bluuebunny/crossref_metadata_2025 huggingface dataset:
Sinbiotik Dari Bawang Putih dan Lactobacillus Acidophilus Terhadap Bobot Badan, Rasio Heterofil: Limfosit dan Suhu Tubuh Ayam Broiler
Authors: Sunu Prayogi , Sunarti Dwi , Yunianto Vitus Dwi , Mahfudz Luthfi Djauhari
Published: August 2024

Tujuan umum penelitian ini adalah untuk mengetahui potensi bawang putih sebagai prebiotik yang dikombinasikan dengan lactobacillus acidhopilus sebagai sinbiotik untuk ayam broiler. Rancangan penelitian dengan RAL, sebagai perlakuan TO = pakan basal; T1= pakan basal + sinbiotik 2 ml; T2= Pakan basal + sinbiotik 4 ml. Parameter yang diamati adalah Performans yang meliputi bobot badan 4 minggu, rasio H/L dan suhu lingkungan. Hasil penelitian menunjukkan bahwa pada perlakuan B dengan 4 mlsinbiotik dapat meningkatkan pertambahan bobot badan sebesar 1202,78 gr. Suhu kandang pada penelitian sekitar 250Câ€“33 0C dengan kelembaban sekitar 45 % - 71 %. Pada rasio H:L meningkat pada perlakuan kontrol secara nyata (P<0,05) dibandingkan perlakuan menggunakan sinbiotik. Suhu Tubuh ayam pada penelitian sekitar 40 0C â€“ 43 0C.
Aplikasi Dekok Daun Kemangi (Ocimum basilicum L) Sebagai Bahan Aktif Untuk Mencegah Kejadian Mastitis Subklinis Pada Sapi Perah
Authors: Faradila Riska , Khopsoh Binti , Lidiyawati Anna
Published: August 2024

Penelitian ini dilakukan untuk mengetahui efektifitas daun kemangi dalam mencegah kejadian mastitis subklinis pada sapi perah dengan menggunakan metode teat dipping. Materi yang digunkan dalam penelitian ini dua belas ekor sapi perah yang menderita mastitis subklinis digunakan dalam rancangan acak kelompok (RAK). Perlakuan berupa teat dipping menggunakan dekok daun kemangi 20%, 30%, 40% dan iodin selama 14 hari. Tingkat kejadian mastitis diketahui dari penjumlahan skor California mastitis test (CMT) dari keempat putting sapi perah. Hasil dari penelitian menunjukkan ada pengaruh nyata (P<0.05) pada setiap konsentrasi dekok daun kemangi dan iodin. kisaran rata-rata skor CMT sebelum teat dipping sebesar 0,96-1,25, kemudian sesudah dilakukan teat dipping selama 14 hari dengan menggunakan dekok daun kemangi kosentrasi 20%, 30%, 40% dan iodin kisaran rata-rata skor CMT turun menjadi 0,42-0,67. Perubahan skor CMT sebelum dan sesudah dilakukan teat dipping selama 14 hari di dapatkan penurunan yang cukup signifikan dengan kisaran 42,74%- 69,72%. Kesimpulan dari penelitian ini dekok daun kemangi dapat digunakan sebagai alternative antiseptik alami untuk mengantikan iodin dalam mencegah kejadian mastitis subklinis pada sapi perah dengan metode teat dipping
DIMENSIONS AFFECTING DIVERSITY MANAGEMENT : A RESEARCH STUDY OF ORGANIZATIONAL MANAGERS IN IT AND NON IT MNC'S OF BANGALORE
Authors: Namrata Kapur  , B Janakiram
Published: August 2024

The greatest challenge of the 21 st century for multinational organizations is the effective management of it's diverse workforce. Demographic changes in workforce composition and customers combined with multicultural workplace congregations have made India to rank in the top globalized markets .This necessiates the increasing amount of diversity the Indian organizations must manage, both internally and externally. This is a descriptive and quantitative research carried out in the IT and non IT cos of India to study the various dimensions of diversity and how the various dimensions viz. Gender, Age, marital status , Education, department, experience, grade level and ethnicity affect the diversity environment in organisations.. A stratified random sampling technique was employed in the present research and the study population consisted of indigenous organizational managers mostly from MNC IT and non IT who engage in leading and managing diverse teams in India .and the results were interpreted using SPSS statistical techniques. The findings highlight that whilst Age, marital status, position, ethnicity and experience have significant correlation with Diversity orientation the gender Education, department, and grade have minimal.Furthermore, it was found that out of the 7 parameters measuring the diversity orientation the Diversity strength, diversity initiatives and diversity popularization were considered as the significant parameters being influenced by these above dimensions while diversity vision and it's business advantage was considered of minimal significance. The. gender (Male/Female), Department (IT/nonIT), Educational level (Engineer/ non Engineer),Position (Manager/ Lead)were greatest common influencers and key dimensions of diversity.
FOREX PERFORMANCE AND BANK PROFITABILITY: AN EVALUATION OF PNB FOREX BRANCH
Authors: Shubhanker Yadav
Published: August 2024

Banks form an essential backbone of the economy. In this era of globalization foreign trade form a signi
Corporate Advertising as a Tool of Corporate Stability- An Analysis of its Effect on Consumers' Attitudes
Authors: Abhishek K. Singh
Published: August 2024

The core outcome of the corporate advertising at the present time of media globalization is to influence the consumer pattern of the market. In developing countries like India, the management of transnational corporations and advertising company are the center of focus as they mainly set the perspective of market developer. It is recognized that corporate advertising are playing a key role in socio-economic development in general and corporate image in particular. Commercial advertising has become a powerful tool in India and other modern organizations. It is very significant as it has proven its importance in the present market system. A large amount of money is provided for the administration of advertising. The present study attempts to analyze, evaluate and discuss appropriate strategies of corporate advertising and its impact on public responses. The research methods used in the present study are mainly conducting (most of the data used are primary in nature)
Exchange Rate and Stock Exchange Indices: An Empirical Study on BSE and NSE Indices
Authors: Suraj Prakash Singh
Published: August 2024

Exchange rate is a key financial change that affects the decisions made by foreign investors, exporters, foreigners, banks, businesses, economic organizations, policy makers and visitors to the developed and developed world. Exchange rate fluctuations affect the number of overseas investment portfolios, shipping and export competition, the value of international reserves, the amount of debt repayments, and the cost to tourists depending on the value of their currency. Exchange rate fluctuations have important effects on the business cycle of the economy, trade and cash flows and therefore it is important to understand financial development and changes in trade and industry policy. Therefore, studying the impact of changes in exchange rates on the Indian stock market is needed. The stock market and foreign
exchange plays an important role in the development of the country. The Asian crisis (1997-1998) is the main reason for establishing a relationship between the exchange rate and the stock price. At this time, the bond market suffered a decline in exchange rates and therefore resulted in a decline in the stock price. So from this, it is understood that although trade flows have a certain impact on the share of corporate stocks, the main source of revenue comes from foreign exchange. Thus, for macro environment the impact of the exchange rate on stock prices depends on global trade and the level of trade imbalance. High intensity in world trade and capital flows have made exchange rates as one of the key determinants of business profitability and equity prices. The present study analyzes the relationship between stock indices and price movements in India. Exchange rate fluctuations have important effects on the business cycle of the economy, trade and cash flows and therefore it is important to understand the financial developments and changes in trade and industry policy. Therefore, studying the impact of changes in exchange rates on the Indian stock market is needed.
Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews
Authors: Matsui Kentaro , Utsumi Tomohiro , Aoki Yumi , Maruki Taku , Takeshima Masahiro , Takaesu Yoshikazu
Published: August 2024

Background

The screening process for systematic reviews is resource-intensive. Although previous machine learning solutions have reported reductions in workload, they risked excluding relevant papers.

Objective

We evaluated the performance of a 3-layer screening method using GPT-3.5 and GPT-4 to streamline the title and abstract-screening process for systematic reviews. Our goal is to develop a screening method that maximizes sensitivity for identifying relevant records.

Methods

We conducted screenings on 2 of our previous systematic reviews related to the treatment of bipolar disorder, with 1381 records from the first review and 3146 from the second. Screenings were conducted using GPT-3.5 (gpt-3.5-turbo-0125) and GPT-4 (gpt-4-0125-preview) across three layers: (1) research design, (2) target patients, and (3) interventions and controls. The 3-layer screening was conducted using prompts tailored to each study. During this process, information extraction according to each study’s inclusion criteria and optimization for screening were carried out using a GPT-4–based flow without manual adjustments. Records were evaluated at each layer, and those meeting the inclusion criteria at all layers were subsequently judged as included.

Results

On each layer, both GPT-3.5 and GPT-4 were able to process about 110 records per minute, and the total time required for screening the first and second studies was approximately 1 hour and 2 hours, respectively. In the first study, the sensitivities/specificities of the GPT-3.5 and GPT-4 were 0.900/0.709 and 0.806/0.996, respectively. Both screenings by GPT-3.5 and GPT-4 judged all 6 records used for the meta-analysis as included. In the second study, the sensitivities/specificities of the GPT-3.5 and GPT-4 were 0.958/0.116 and 0.875/0.855, respectively. The sensitivities for the relevant records align with those of human evaluators: 0.867-1.000 for the first study and 0.776-0.979 for the second study. Both screenings by GPT-3.5 and GPT-4 judged all 9 records used for the meta-analysis as included. After accounting for justifiably excluded records by GPT-4, the sensitivities/specificities of the GPT-4 screening were 0.962/0.996 in the first study and 0.943/0.855 in the second study. Further investigation indicated that the cases incorrectly excluded by GPT-3.5 were due to a lack of domain knowledge, while the cases incorrectly excluded by GPT-4 were due to misinterpretations of the inclusion criteria.

Conclusions

Our 3-layer screening method with GPT-4 demonstrated acceptable level of sensitivity and specificity that supports its practical application in systematic review screenings. Future research should aim to generalize this approach and explore its effectiveness in diverse settings, both medical and nonmedical, to fully establish its use and operational feasibility.
Impact of Skin Pigmentation on Pulse Oximetry Blood Oxygenation and Wearable Pulse Rate Accuracy: Systematic Review and Meta-Analysis
Authors: Singh Sanidhya , Bennett Miles Romney , Chen Chen , Shin Sooyoon , Ghanbari Hamid , Nelson Benjamin W
Published: August 2024

Background

Photoplethysmography (PPG) is a technology routinely used in clinical practice to assess blood oxygenation (SpO2) and pulse rate (PR). Skin pigmentation may influence accuracy, leading to health outcomes disparities.

Objective

This systematic review and meta-analysis primarily aimed to evaluate the accuracy of PPG-derived SpO2 and PR by skin pigmentation. Secondarily, we aimed to evaluate statistical biases and the clinical relevance of PPG-derived SpO2 and PR according to skin pigmentation.

Methods

We identified 23 pulse oximetry studies (n=59,684; 197,353 paired SpO2-arterial blood observations) and 4 wearable PR studies (n=176; 140,771 paired PPG-electrocardiography observations). We evaluated accuracy according to skin pigmentation group by comparing SpO2 accuracy root-mean-square values to the regulatory threshold of 3% and PR 95% limits of agreement values to +5 or –5 beats per minute (bpm), according to the standards of the American National Standards Institute, Association for the Advancement of Medical Instrumentation, and the International Electrotechnical Commission. We evaluated biases and clinical relevance using mean bias and 95% CI.

Results

For SpO2, accuracy root-mean-square values were 3.96%, 4.71%, and 4.15%, and pooled mean biases were 0.70% (95% CI 0.17%-1.22%), 0.27% (95% CI –0.64% to 1.19%), and 1.27% (95% CI 0.58%-1.95%) for light, medium, and dark pigmentation, respectively. For PR, 95% limits of agreement values were from –16.02 to 13.54, from –18.62 to 16.84, and from –33.69 to 32.54, and pooled mean biases were –1.24 (95% CI –5.31 to 2.83) bpm, –0.89 (95% CI –3.70 to 1.93) bpm, and –0.57 (95% CI –9.44 to 8.29) bpm for light, medium, and dark pigmentation, respectively.

Conclusions

SpO2 and PR measurements may be inaccurate across all skin pigmentation groups, breaching U.S. Food and Drug Administration guidance and industry standard thresholds. Pulse oximeters significantly overestimate SpO2 for both light and dark skin pigmentation, but this overestimation may not be clinically relevant. PRs obtained from wearables exhibit no statistically or clinically significant bias based on skin pigmentation.
Human-Comparable Sensitivity of Large Language Models in Identifying Eligible Studies Through Title and Abstract Screening: 3-Layer Strategy Using GPT-3.5 and GPT-4 for Systematic Reviews (Preprint)
Authors: Matsui Kentaro , Utsumi Tomohiro , Aoki Yumi , Maruki Taku , Takeshima Masahiro , Takaesu Yoshikazu
Published: August 2024

BACKGROUND

The screening process for systematic reviews is resource-intensive. Although previous machine learning solutions have reported reductions in workload, they risked excluding relevant papers.

OBJECTIVE

We evaluated the performance of a 3-layer screening method using GPT-3.5 and GPT-4 to streamline the title and abstract-screening process for systematic reviews. Our goal is to develop a screening method that maximizes sensitivity for identifying relevant records.

METHODS

We conducted screenings on 2 of our previous systematic reviews related to the treatment of bipolar disorder, with 1381 records from the first review and 3146 from the second. Screenings were conducted using GPT-3.5 (gpt-3.5-turbo-0125) and GPT-4 (gpt-4-0125-preview) across three layers: (1) research design, (2) target patients, and (3) interventions and controls. The 3-layer screening was conducted using prompts tailored to each study. During this process, information extraction according to each study’s inclusion criteria and optimization for screening were carried out using a GPT-4–based flow without manual adjustments. Records were evaluated at each layer, and those meeting the inclusion criteria at all layers were subsequently judged as included.

RESULTS

On each layer, both GPT-3.5 and GPT-4 were able to process about 110 records per minute, and the total time required for screening the first and second studies was approximately 1 hour and 2 hours, respectively. In the first study, the sensitivities/specificities of the GPT-3.5 and GPT-4 were 0.900/0.709 and 0.806/0.996, respectively. Both screenings by GPT-3.5 and GPT-4 judged all 6 records used for the meta-analysis as included. In the second study, the sensitivities/specificities of the GPT-3.5 and GPT-4 were 0.958/0.116 and 0.875/0.855, respectively. The sensitivities for the relevant records align with those of human evaluators: 0.867-1.000 for the first study and 0.776-0.979 for the second study. Both screenings by GPT-3.5 and GPT-4 judged all 9 records used for the meta-analysis as included. After accounting for justifiably excluded records by GPT-4, the sensitivities/specificities of the GPT-4 screening were 0.962/0.996 in the first study and 0.943/0.855 in the second study. Further investigation indicated that the cases incorrectly excluded by GPT-3.5 were due to a lack of domain knowledge, while the cases incorrectly excluded by GPT-4 were due to misinterpretations of the inclusion criteria.

CONCLUSIONS

Our 3-layer screening method with GPT-4 demonstrated acceptable level of sensitivity and specificity that supports its practical application in systematic review screenings. Future research should aim to generalize this approach and explore its effectiveness in diverse settings, both medical and nonmedical, to fully establish its use and operational feasibility.
A Language Model–Powered Simulated Patient With Automated Feedback for History Taking: Prospective Study (Preprint)
Authors: Holderried Friederike , Stegemann-Philipps Christian , Herrmann-Werner Anne , Festl-Wietek Teresa , Holderried Martin , Eickhoff Carsten , Mahling Moritz
Published: August 2024

BACKGROUND

Although history taking is fundamental for diagnosing medical conditions, teaching and providing feedback on the skill can be challenging due to resource constraints. Virtual simulated patients and web-based chatbots have thus emerged as educational tools, with recent advancements in artificial intelligence (AI) such as large language models (LLMs) enhancing their realism and potential to provide feedback.

OBJECTIVE

In our study, we aimed to evaluate the effectiveness of a Generative Pretrained Transformer (GPT) 4 model to provide structured feedback on medical students’ performance in history taking with a simulated patient.

METHODS

We conducted a prospective study involving medical students performing history taking with a GPT-powered chatbot. To that end, we designed a chatbot to simulate patients’ responses and provide immediate feedback on the comprehensiveness of the students’ history taking. Students’ interactions with the chatbot were analyzed, and feedback from the chatbot was compared with feedback from a human rater. We measured interrater reliability and performed a descriptive analysis to assess the quality of feedback.

RESULTS

Most of the study’s participants were in their third year of medical school. A total of 1894 question-answer pairs from 106 conversations were included in our analysis. GPT-4’s role-play and responses were medically plausible in more than 99% of cases. Interrater reliability between GPT-4 and the human rater showed “almost perfect” agreement (Cohen κ=0.832). Less agreement (κ<0.6) detected for 8 out of 45 feedback categories highlighted topics about which the model’s assessments were overly specific or diverged from human judgement.

CONCLUSIONS

The GPT model was effective in providing structured feedback on history-taking dialogs provided by medical students. Although we unraveled some limitations regarding the specificity of feedback for certain feedback categories, the overall high agreement with human raters suggests that LLMs can be a valuable tool for medical education. Our findings, thus, advocate the careful integration of AI-driven feedback mechanisms in medical training and highlight important aspects when LLMs are used in that context.
Teledentistry for improving access to, and quality of oral health care: An overview of systematic reviews and meta-analyses (Preprint)
Authors: Kengne Talla Pascaline , Allison Paul , Bussières André , Rodrigues Anisha , Bergeron Frédéric , Giraudeau Nicolas , Emami Elham
Published: August 2024

BACKGROUND

Digital interventions including teleledentistry are promising approaches to address some of the inadequacies of healthcare systems. Despite systematic reviews (SRs) on the benefits and implementation challenges of teledentistry, its impact on the quality of care remains unclear.

OBJECTIVE

The purpose of this overview of SRs is to summarize evidence on the impact of teledentistry in promoting access to and enhancing the quality of oral health care.

METHODS

We searched electronic databases in MEDLINE (Ovid), Embase (Embase.com), CINAHL (EBSCO), Web of Science, Cochrane Library, Epistemonikos and grey literature to identify SRs and meta-analysis of quantitative, qualitative, and mixed reviews, with the support of an expert librarian, from inception to March 2024. In addition, we checked the reference lists of included SRs. We included studies without data and language restrictions. Two independent reviewers performed data screening and data extraction and assessed the quality of included SRs using the AMSTAR 2 and ROBIS tools. We assessed the overlap of the included reviews. We reported on the certainty of evidence and on the heterogeneity from the included studies. Data are synthesized narratively and presented with tables and graphs.

RESULTS

The search yielded 1020 articles, of which 30 SRs were included in the overview. The number of participants across these reviews ranged from 130 to 7913 people. All dimensions of the quality of care were addressed to varying extents, with the domains of effectiveness, efficiency, and patient-centered care being the most extensively studied. Conversely, patient safety and equity were the least explored domains. Several SRs exhibited a critically low to low methodological quality and a high risk of bias. The overlap (corrected covered area) of the primary studies in all the SRs was slight (2.3%), while it as moderate (5.7%) for SRs with meta-analysis (SR-MAs).

CONCLUSIONS

The findings of this overview suggest that teledentistry is an effective and efficient alternative to in-person oral health care, in line with the Quintuple Aim. However, concerns with the quality of the reviews warrant a call for more rigorous studies to obtain more robust evidence, notably on its potential to achieve equity.
Understanding Acceptance of Healthcare Technology Among Older Adults Through TAM and UTAUT: Systematic Review and Meta-Analysis (Preprint)
Authors: Yang Hyo Jun , Lee Ji-Hyun , Lee Wonjae
Published: August 2024

BACKGROUND

To understand the acceptance of healthcare technology for older adults, the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) is commonly used. However, the divergence in the current literature makes it difficult to predict acceptance and understand how various factors affect older adults’ behavior.

OBJECTIVE

This study aims to 1) determine the influence of perceived usefulness (PU), perceived ease of use (PEOU), and social influence (SI) on the behavioral intention (BI) to use healthcare technology among older adults and 2) and assess the moderating effects of age, gender, geographic region, type of healthcare technology, and the presence of visual demonstrations on these three pairwise relationships.

METHODS

Google Scholar, Web of Science, Scopus, IEEE Xplore, and ProQuest electronic databases were searched from inception to February 2024. Two independent reviewers screened the titles, abstracts, full texts, and performed data extraction and risk of bias assessments with the Newcastle-Ottawa Quality Assessment Scale. The "meta" package in R was used for data synthesis, conducting random-effects meta-analyses, meta-regression and subgroup analysis.

RESULTS

41 studies with a total of 11,574 participants were included. Random-effects meta-analyses showed significant positive correlations for PU-BI (r = 0.607, 95% CI 0.543 - 0.665, P < .001), PEOU-BI (r = 0.525, 95% CI 0.462 - 0.583, P < .001), and SI-BI (r = 0.551, 95% CI 0.468 - 0.624, P < .001). Moderator analyses indicated significant differences in effect sizes based on geographic region for PEOU-BI (Q-test, P = .04), type of technology for PU-BI (Q-test, P = .04) and SI-BI (Q-test, P = .002), and presence of visual demonstrations for PU-BI (Q-test, P = .03) and SI-BI (Q-test, P = .04).

CONCLUSIONS

The findings indicate that PU, PEOU, SI significantly impact the acceptance of healthcare technology among older adults, with heterogeneity influenced by geographic region, type of technology, and presence of visual demonstrations. Researchers should account for these variables when interpreting previous research and embarking on new studies with the TAM or UTAUT model for older adults.

CLINICALTRIAL

Current paper is not RCT
Understanding Intimate Health in Public Spaces: A Study Protocol (Preprint)
Authors: Egli Victoria , Vandewiele Callie , Price Hanna , MacIntyre Caitlyn , Bickerton Sarah , Duggan Nina , McNamee Seline , Rakete Emmy , Cavadino Alana
Published: August 2024

BACKGROUND

Social media has become an important tool facilitating communication and connection in a post-pandemic landscape. This context has prompted an increase in the sharing of information and disinformation about general health, and provides an opportunity to seek information about and support for intimate health with the added assurance of maintaining a degree of anonymity in a socially taboo context.

OBJECTIVE

The aim of this study is to better understand how women in Aotearoa New Zealand use social media to access sexual and reproductive health information and support. Engagement with stakeholders and community groups will be undertaken throughout the study to analyse the findings therein, and present solutions to identified issues.

METHODS

This study uses a mixed-methods approach, involving the collection of qualitative and quantitative data through an anonymous survey on the Qualtrics Survey Software platform. Recruitment will occur through advertising on University social media accounts, and physical posters in various locations nationwide, prioritising often-underrepresented groups. This study will also present the preliminary results to stakeholders, prioritising whakawhanaungatanga and manaakitanga in the co-designing of future research aims. Subsequent analysis of all the above data forms will be performed, with dissemination of results in academic, participant, and stakeholder circles.

RESULTS

Ethical approval to conduct this study was granted by the University ethical review board on June 23rd, 2023 and an amendment to change survey questions and expand recruitment was submitted June 5th, 2024. Data collection will occur until June 2025 with stakeholder engagement occurring throughout.

CONCLUSIONS

None
In the Face of Confounders: Atrial Fibrillation Detection – Practitioners vs. ChatGPT (Preprint)
Authors: Avidan Yuval , Tabachnikov Vsevolod , Ben Court Orel , Khoury Razi , Aker Amir
Published: August 2024

BACKGROUND

Atrial fibrillation (AF) is the most common arrhythmia in clinical practice, yet interpretation concerns among healthcare providers persist. Confounding factors contribute to false-positive and false-negative AF diagnoses, leading to potential omissions. Artificial intelligence advancements show promise in electrocardiogram (ECG) interpretation.

OBJECTIVE

We sought to examine the diagnostic accuracy of ChatGPT-4omni (GPT-4o), equipped with image evaluation capabilities, in interpreting ECGs with confounding factors and compare its performance to that of physicians.

METHODS

Twenty ECG cases, divided into Group A (10 cases of AF or atrial flutter) and Group B (10 cases of sinus or another atrial rhythm), were crafted into multiple-choice questions. Total of 100 practitioners (25 from each: emergency medicine, internal medicine, primary care, and cardiology) were tasked to identify the underlying rhythm. Next, GPT-4o was prompted in five separate sessions.

RESULTS

GPT-4o performed inadequately, averaging 3 (±2) in Group A questions and 5.40 (±1.34) in Group B questions. Upon examining the accuracy of the total ECG questions, no significant difference was found between GPT-4o, internists, and primary care physicians (p = 0.952 and = 0.852, respectively). Cardiologists outperformed other medical disciplines and GPT-4o (p < 0.001), while emergency physicians followed in accuracy, though comparison to GPT-4o only indicated a trend (p = 0.068).

CONCLUSIONS

GPT-4o demonstrated suboptimal accuracy with significant under- and over-recognition of AF in ECGs with confounding factors. Despite its potential as a supportive tool for ECG interpretation, its performance did not surpass that of medical practitioners, underscoring the continued importance of human expertise in complex diagnostics.
Impact of Internet Usage on Depression Among Older Adults: Comprehensive Study (Preprint)
Authors: Guo Lin , Li Yunwei , Cheng Kai , Zhao Ying , Yin Wenqiang , Liu Ying
Published: August 2024

BACKGROUND

Depression is a widespread mental health issue affecting older adults globally, with substantial implications for their well-being. Although digital interventions have proven effective in high-income countries, research on the potential of internet usage to alleviate depression among older adults in high-income countries remains limited.

OBJECTIVE

This study aimed to examine the impact of internet usage on depression among older adults in high-income countries by developing a comprehensive theoretical framework and testing key hypotheses.

METHODS

Using data from the China Health and Retirement Longitudinal Study (CHARLS), a 2-stage instrumental variable approach was applied to address endogeneity and estimate causal relationships between internet usage and depression.

RESULTS

The findings indicate that internet usage results in a 1.41% reduction in depression levels among older adults. This effect is mediated by four primary mechanisms: (1) enhanced social interaction, (2) increased physical activity, (3) improved intergenerational contact, and (4) expanded access to educational opportunities. A heterogeneity analysis revealed that these effects are more pronounced in urban areas, eastern regions, and regions with superior internet infrastructure.

CONCLUSIONS

Internet usage plays a crucial role in alleviating depression among older adults in high-income countries, with regional variations. The findings highlight the need for targeted policy interventions to improve internet access and digital literacy, which can mitigate depression and enhance the mental health of older adults.
Consistency of daily number of reported COVID-19 cases in 191 countries between two major data sources, 2020-2022 (Preprint)
Authors: Liu Han , Zong Huiying , Yang Yang , Schwebel David C , Xie Bin , Ning Peishan , Rao Zhenzhen , Li Li , Hu Guoqing
Published: August 2024

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic is among the greatest global public health challenges of this century.The WHO and the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) were two open-access data sources which were widely used in research and decision-making about the COVID-19 epidemic.High-quality data is one key aspect of public health crisis and pandemic preparedness for decision-making, practice, and research about prevention and control. To better respond to pandemics and other health crises in the future, it is necessary to evaluate the quality of pandemic data to improve rapid response to outbreaks.

OBJECTIVE

To evaluate consistency of daily reported Coronavirus disease 2019 (COVID-19) cases in 191 countries from the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) and the World Health Organization (WHO) dashboards during 2020-2022.

METHODS

We retrieved data concerning new daily COVID-19 cases in 191 countries covered by both data sources from January 22, 2020, to December 31, 2022. The ratio of numbers of daily reported cases from the two sources were calculated to measure data consistency. We performed simple linear regression to examine significant changes in the ratio of numbers of daily reported cases during the study period.

RESULTS

Of 191 WHO member countries, only 60 displayed excellent data consistency in the number of daily reported COVID-19 cases between the WHO and JHU CSSE dashboards (case number ratio: 0.9-1.1). Data consistency changed greatly across the 191 countries from 2020 to 2022 and differed across four types of countries, defined by income. Data inconsistency between the two data sources generally decreased slightly over time, both for the 191 countries combined and within the four types of income-defined countries. The absolute relative difference between two data sources increased in 84 countries (particularly for Malta, Montenegro, and United States, R2=0.29) but decreased in 40 countries (P<0.05).

CONCLUSIONS

The inconsistency between the two data sources warrants further research. Construction of public health surveillance and data collection systems for public health emergencies like the COVID-19 pandemic should be strengthened in the future.
Machine Learning in Genomic Data Analysis for Personalized Medicine
Authors: Saraswat Aayushi , Roopesh Shrikanth
Published: August 2024

Abstract: The advent of precision medicine marks a transformative shift from traditional symptom-based treatments to more personalized approaches that account for individual genetic variations. Central to this evolution is the integration of genomic data, which offers profound insights into the biological underpinnings of disease and enables the development of targeted therapies. Machine learning (ML) has emerged as a pivotal tool in this domain, capable of deciphering complex patterns in high-dimensional genomic data, thereby enhancing early disease risk prediction and informing tailored therapeutic strategies. This review explores the intersection of machine learning and genomic medicine, highlighting how advanced computational techniques, including deep learning and other ML approaches, are driving innovation in personalized healthcare. By examining the application of these technologies in areas such as disease risk assessment, precision oncology, and pharmacogenomics, this paper elucidates the current state of the field and identifies future directions for research. Ethical considerations, such as data privacy, model transparency, and bias mitigation, are also discussed, emphasizing the need for responsible and equitable implementation of ML in clinical practice. Through this analysis, the paper aims to underscore the potential of machine learning to revolutionize personalized medicine and improve patient outcomes.
Developing storytelling for tour guide to build global branding in Desa Wisata Jajar Gumregah
Authors: Wahyuningtyas Dwi , Hamidah Nuriyatul , Sumarno Wahyu Kyestiati , Yurenaudia Azzahra , Maharani Dian Sasmitha Dwi , Trirahardjo Muhammad Rizqy
Published: August 2024

Trenggalek has more than 30 tourist villages that have been intensively built since 2020, including Desa Wisata Jajar Gumregah. This village was chosen as one of the 300 best tourism villages in Anugerah Desa Wisata (ADWI) 2023. This year, one of the tourist villages proposed by the Trenggalek government was Desa Wisata Jajar Gumregah. This tourist village has much potential for development, including cultural tourism. Cultural tourism in this tourist village can be developed into storynomics tourism. To develop storynomics tourism in Desa Wisata Jajar Gumregah, the community service team from UPN “Veteran” Jawa Timur then initiated and held a program called “Storytelling for Tour Guide” in Desa Wisata Jajar Gumregah, Trenggalek. The program was successfully held on the 25th – 26th of June 2023 at Pendopo Desa Wisata Jajar Gumregah, attended by around 35 participants. They came from diverse backgrounds, from senior high school to undergraduate level. The success was proven by the participation and involvement of the participants in the discussion sessions and the publications made. In the future, the improvement of the storytelling skills of tour guides can boost the tourism sector in the area.
Perancangan Aplikasi Mobile Untuk Pemesanan Tiket Kereta Menggunakan UX Journey
Authors: Atharidi Thirafi Buana
Published: August 2024

Technology for booking train tickets salah satu jenis pelayanan yang diberikan negara untuk masyarakatnya adalah pelayanan transportasi diantaranya ialah Kereta Api. Jumlah pengguna jasa transportasi kereta api setiap tahunnya terus mengalami peningkatan. Aplikasi E- Ticket Train Booking merupakan salah satu aplikasi pemesanan tiket secara online Aplikasi E-Ticket Train Booking ini bertujuan untuk memudahkan konsumennya dalam melakukan pembelian. Tujuan Penelitian ini adalah merancang, mengetahui dan menganalisis faktor yang mempengaruhi perilaku konsumen dalam keputusannya membeli tiket kereta api masih dengan cara konvensional serta mengetahui keefektifan aplikasi E-Ticket Train Booking oleh konsumen tersebut. Rancangan penelitian ini menggunakan Metode: penelitian yang digunakan yaitu UX Jouney. Populasi dalam penelitian ini yaitu konsumen dengan jumlah partisipan 5 orang. Penelitian dilakukan dengan metode wawancara, observasi dan studi pustaka. Hasil wawancara dilakukan reduksi data, disajikan dan ditarik kesimpulan. Hasil penelitian didapatkan 5 faktor yang mempengaruhi perilaku konsumen dalam keputusannya membeli tiket masih dengan cara konvensional dan hasil persepsi seluruh konsumen yang menilai dan memilih pembelian tiket secara konvensional lebih baik, dapat disimpulkan dan pengembangan aplikasi E-Ticket Train Booking belum efektif dimanfaatkan oleh konsumen yang masih membeli tiket langsung di loket stasiun. Diharapkan pengembang bisa terus mempertahankan dan meningkatkan fitur-fitur yang telah dinilai positif oleh persona.
Analisis Sentimen Twitter terhadap Isu Penundaan Pemilu 2024 Menggunakan Metode Long Short-Term Memory (LSTM)
Authors: Prasetyo Andy Putra , Sri Kusuma Christian , Rizki Didih
Published: August 2024

Media sosial adalah bentuk aktivitas sosial yang menggunakan jaringan online untuk berkomunikasi melalui teks, gambar, dan video. Salah satu platform media sosial yang tetap menjadi tempat ekspresi bebas bagi individu adalah Twitter. Penelitian ini mengkaji sentimen masyarakat di Twitter terkait isu penundaan pemilu 2024 di Indonesia. Fokus utama penelitian ini adalah untuk menganalisis pandangan publik terhadap isu tersebut menggunakan metode Long Short-Term Memory (LSTM) dalam analisis sentimen. Data yang digunakan berasal dari cuitan-cuitan yang terkait dengan isu penundaan pemilu di Twitter. Tujuan penelitian ini adalah untuk memahami sejauh mana sentimen masyarakat terhadap isu penundaan pemilu 2024, apakah bersifat positif, negatif, atau netral. Metode yang digunakan adalah LSTM, sebuah teknik deep learning yang digunakan untuk memproses data teks dalam urutan. Data yang digunakan mencakup 1758 sampel setelah melalui proses pra-pemrosesan. Hasil penelitian menunjukkan bahwa sebanyak 58,0% dari sampel menunjukkan sentimen positif, sementara 42,0% menunjukkan sentimen negatif. Model LSTM yang diterapkan berhasil mencapai tingkat akurasi sebesar 88% dalam mengklasifikasikan sentimen masyarakat di Twitter terkait isu penundaan pemilu. Kesimpulan penelitian ini adalah mayoritas masyarakat yang terlibat dalam percakapan di Twitter terkait isu penundaan pemilu 2024 menunjukkan sentimen positif. Namun, masih ada sebagian yang menunjukkan sentimen negatif. Tingkat akurasi model LSTM yang tinggi menunjukkan efektivitas metode ini dalam menganalisis data teks dari media sosial. Oleh karena itu, penelitian ini memberikan wawasan yang berharga tentang pandangan publik terhadap isu penting ini diera digital.
Penerapan Metode Fuzzy Logic Pada Rancang Bangun Tempat Sampah Pintar dengan Sistem Monitoring Berbasis Cloud dan Internet of Things (IoT)
Authors: Arya Santika Dimas , Sari Zamah , Akbi Denar Regata
Published: August 2024

Petugas kebersihan terkadang mengalami keterlambatan dalam melakukan pembersihan tempat sampah karena pemeriksaan tempat sampah dilakukan secara manual. Hal ini kurang efektif karena dapat mengakibatkan penumpukan sampah yang dapat menimbulkan bau dan penyakit. Oleh karena itu penelitian ini bertujuan untuk meningkatkan efesiensi pada pengelolaan sampah. Metode penelitian yang digunakan pada penelitian ini berupa rancang bangun yang melibatkan analisa kebutuhan, desain, perancangan sistem, dan pengujian sistem. Pada penelitian ini dirancang sebuah sistem monitoring tempat sampah dengan menggunakan ESP32 sebagai mikrokontroller, sensor HC-SR04 untuk mendeteksi kapasitas tempat sampah dan sensor MQ-135 untuk mendeteksi kandungan gas ammonia dalam sampah. Sistem dapat mengetahui kapasitas tempat sampah, waktu terakhir pembersihan, dan bau ammonia pada sampah. Penentuan tindakan pengambilan sampah dilakukan menggunakan metode fuzzy logic dengan ketepatan dalam penentuan tindakan sebesar 100% yang akan dikirimkan melalui notifikasi telegram.
Passageiros que não pagam passagem: reflexões sobre conexões entre circulação urbana e privação de liberdade
Authors: Martins Luana Almeida
Published: August 2024

Os espaços de privação de liberdade têm sido pensados cada vez mais não só como instituições totais apartadas da vida urbana, mas também através de seus fluxos, da circulação ou da porosidade. Essas reflexões vão desde as relações entre pessoas que circulam entre o dentro e o fora da prisão até a maneira como a administração das unidades de privação de liberdade funciona. A partir de uma pesquisa etnográfica realizada em uma unidade socioeducativa de internação provisória, pude observar como essa porosidade pode ser pensada não só por suas dimensões estáticas, mas também pelo foco na circulação urbana, mais especificamente a partir do trajeto de um transporte público coletivo. Nesse sentido, neste artigo busco refletir sobre a relação entre a circulação urbana, a segurança pública e o sistema socioeducativo a partir de relatos de meus interlocutores sobre uma linha de ônibus específica que conecta a Zona Sul e a Zona Norte da cidade do Rio de Janeiro e por vezes acaba por criar outros pontos de conexão: a prisão para esses adolescentes que se representam como passageiros que não pagam a passagem. Assim, tratarei de questões que se relacionam não só com o controle social e o crime, mas também da circulação de determinados grupos pela cidade e sua relação com a privação de liberdade.
Penggunaan metode jarimatika untuk meningkatkan kemampuan berhitung perkalian peserta didik kelas III SD
Authors: Della Rosaline  , Yusuf Suryana  , Muhammad Rijal Wahid Muharram
Published: August 2024

Penelitian ini bertujuan untuk mengetahui peningkatan kemampuan berhitung perkalian peserta didik kelas III Sekolah Dasar. Penelitian ini berfokus pada penggunaan Jarimatika untuk membantu peserta didik dalam menyelesaikan soal perkalian. Hal ini didasari oleh kondisi faktual dimana peserta didik belum mampu mengerjakan perkalian bilangan dan juga metode pembelajaran yang diterapkan monoton membuat pembelajaran matematika terasa sulit. Penelitian ini menggunakan metode eksperimen dengan desain quasi eksperimen berupa nonequivalent control group design. Kelas eksperimen diberi perlakuan dengan metode jarimatika, sedangkan kelas kontrol tanpa menggunakan metode jarimatika. Teknik pengumpulan data dalam penelitian ini menggunakan tes. Hasil penelitian menunjukan bahwa terdapat peningkatan kemampuan berhitung perkalian peserta didik yang dapat dilihat dari hasil uji N-Gain. Berdasarkan hasil uji N-Gain, nilai rata-rata N-gain Score untuk kelas eksperimen sebesar 68,9012 atau 69% dimana 69% termasuk kedalam kategori cukup efektif. Sedangkan nilai rata-rata N-gain Score pada kelas kontrol sebesar 35,4188 atau 35% dimana 35% termasuk kedalam kategori tidak efektif. Kemudian dilakukan uji-t terhadap data N-gain Score, diperoleh hasil nilai Sig. (2-tailed) sebesar 0,000. Hal tersebut menunjukan bahwa 0,000 < 0,05 yang berarti Ha diterima H0 ditolak, sehingga dapat disimpulkan bahwa peningkatan kemampuan berhitung perkalian peserta didik yang memperoleh pembelajaran menggunakan metode jarimatika lebih tinggi daripada peserta didik yang memperoleh pembelajaran tanpa menggunakan metode jarimatika.
E-modul permainan tradisional gobak sodor bermuatan karakter di sekolah dasar
Authors: Tantri Dwi Lestari  , Hidayat Syarip , Ganda Nana
Published: August 2024

Abstrak
Tujuan penelitian ini yaitu mengembangkan e-modul permainan tradisional permainan tradisional gobak sodor bermuatan karakter untuk siswa sekolah dasar. Model penelitian yang digunakan yaitu penelitian dan pengembangan dengan menggunakan Langkah-langkah penelitian ripe ADDIE, yaitu Analyze, Design, Development, Implementation, dan Evaluation. Penelitian ini melibatkankan guru yang berasal dari salah satu sekolah dasar di Desa Gesik, Kecamatan Tengah Tani, Kabupaten Cirebon sebagai informan untuk analisis kebutuhan, tiga validator e-modul yang terdiri dari satu orang validator ahli media, satu orang validator ahli pedagogik, dan ahli pendidikan karakter. Validasi e-modul ini menggunakan skala 1-4 untuk penilaiannya, secara keseluruhan e-modul yamg telah dikembangkan mendapatkan hasil penilaian kategori sangat layak dengan presentase rata-rata 88,83% pada validasi ahli pedagogik, dan presentase rata-rata 90,1% dengan kategori sangat layak pada validasi ahli media, dan memperoleh rata-rata presentase 66,67 dengan kategori cukup layak pada validasi ahli pendidikan karakter. Sehingga berdasarkan hasil validasi ahli e-modul ini layak digunakan dengan revisi. Penelitian ini dilakukan dengan dua kali uji coba dengan jumlah responden 26 siswa dalam satu rombel.
 
Kata Kunci: E-modul, Permainan Tradisional, Pendidikan karakter
Peningkatan kerjasama dan hasil belajar menggunakan model problem based learning pada siswa kelas III SD
Authors: Ajeng Wuri Puspita Lusia  , Rusmawan  , Kurniastuti Dianing
Published: August 2024

Penelitian ini dilatarbelakangi oleh rendahnya kerjasama dan hasil belajar siswa kelas III SD. Penelitian ini bertujuan untuk meningkatkan kerjasama dan hasil belajar bagi siswa kelas III SD melalui penerapan model problem based learning. Jenis penelitian yang digunakan yaitu penelitian tindakan kelas dalam dua siklus. Subjek penelitian ini adalah siswa kelas III SD. Instrumen yang digunakan tes dan non tes. Data dikumpulkan dengan menggunakan soal evaluasi untuk mengetahui hasil belajar dan lembar observasi untuk mengamati kerjasama siswa. Hasil dari penelitian ini menunjukkan nilai rata-rata kerjasama siswa mengalami peningkatan dari 54 dalam kategori rendah menjadi 67 pada siklus I dalam kategori tinggi, dan meningkat kembali menjadi 74 dalam kategori tinggi pada siklus II. Peningkatan terjadi pula pada hasil belajar siswa dari persentase ketuntasan klasikal dari 38% meningkat menjadi 54% pada siklus I, dan meningkat kembali menjadi 85% pada siklus II. Hasil penelitian ini menunjukkan bahwa penerapan model problem based learning dapat meningkatkan kerjasama dan hasil belajar siswa.
Analisis implementasi program adiwiyata dalam menanamkan karakter peduli lingkungan pada siswa di sekolah dasar
Authors: Esa Lestari Putri , Mulyadiprana Ahmad , Setiadi Pidi Mohamad
Published: August 2024

Permasalahan lingkungan mendapatkan perhatian khusus dari pemerintah maupun masyarakat, karena banyaknya bencana dan kerusakan yang terjadi akibat ulah manusia. Oleh karena itu, Kementrian Lingkungan Hidup dengan Departemen Pendidikan Nasional membentuk program Adiwiyata untuk mewujudkan warga sekolah yang bertanggung jawab dalam upaya perlindungan dan pengelolaan lingkungan melalui tata kelola sekolah yang baik. Penelitian ini bertujuan untuk menganalisis penanaman karakter peduli lingkungan pada siswa melalui program Adiwiyata di SDN 8 Panjalu. Metode yang digunakan dalam penelitian ini adalah metode studi kasus dengan pendekatan kualitatif deskripstif. Teknik pengumpulan data yang digunakan meliputi observasi, wawancara, dan dokumentasi. Data yang diperoleh kemudian dianalisis menggunakan cara reduksi data, display data, dan verifikasi data. Hasil penelitian menunjukkan bahwa 1) perencanaan program Adiwiyata telah dilaksanakan dengan baik yang melibatkan semua stakeholder sekolah, 2) pelaksanaan program Adiwiyata dilaksanakan melalui berbagai kegiatan seperti melaksanakan jadwal piket dan ikut serta dalam kegiatan gebyar lingkungan, 3) implikasi dari adanya program Adiwiyata dapat menumbuhkan kepekaan dan kepeduliaan siswa terhadap lingkungan, 4) faktor pendukung berasal dari sarana prasana yang memadai dan bimbingan yang senantiasa diberikan oleh guru kepada siswa, sedangkan faktor penghambatnya terjadi akibat adanya Covid-19 yang mempengaruhi terhadap sikap siswa dan lingkungan sekolah.