bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping Actionable Gaps in Patient Journey for Depression in the United Arab
Emirates: A Strategic Framework
Authors: Makhoul Samer , Ali Osama , Nayaz Ahmed Nahida , Siddiqui Urooj , Cherchali Amina 
Published: February 2024

Background:
Depression is on a steady rise across the United Arab Emirates (UAE), causing much socio-economic burden to the country. Identifying patient
journey gaps for depression, beginning with awareness and screening, diagnosis, and treatment to sustained remission and rehabilitation, can help
design health policies with actionable solutions, mitigating the burden of the disease.

Methods:
Studies in the English language between 2010 and 2021 were shortlisted using a structured search in electronic databases followed by an
unstructured search using government websites and Google Scholar and anecdotal data from local professional experts. Synthesized data was
subjected to weighted mean calculation, and an evidence gap map was charted.

Results:
Varying prevalence of depression (5.1%-82.2%) was reported across different settings and population sample sizes in the UAE. One study reported
that 13.0% of the UAE population was aware of their depressive condition. Screening rates of depression were reported to be relatively high
(34.2%-90.5%), while depression was diagnosed in 0.5%-48.5% of patients. The treatment rate was 36.1%, while adherence rates were estimated
to be low at 0.3%. No evidence of control or remission of depression could be gathered.

:
The reviewed studies used only the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for diagnosing depression.
The review also lacked large-scale research studies that may have limited the actual representation of the prevalence of depression across the
country.

Conclusion:
Addressing the gaps identified through evidence mapping methodology can shape a ‘model of care’ for depression. This model should aim to
harmonize collaborations among the mental health stakeholders and advocate for the social reintegration of patients.
Artificial Intelligence and Cardiovascular Diseases
Authors: Younes Rami , Almaghraby Abdallah 
Published: February 2024

Abstract:
Artificial intelligence (AI) has reshaped significant aspects of our lives, including its role in healthcare.

:
AI is a machine-based system that can make predictions, recommendations, and decisions influencing real or virtual environments of a given set of
human-defined objectives. It is designed to operate with varying levels of autonomy.

:
Since cardiovascular medicine is rapidly progressing and new technologies are introduced to cardiovascular tools, AI has become valuable in
cardiovascular medicine. This narrative review will discuss the general concept of AI and its role in diagnosing cardiovascular diseases, including
ECG, echocardiography, cardiac CT, nuclear cardiology, cardiac MRI, cardiac catheterization, electrophysiology, heart failure, clinical decision
support system, and face recognition.
Fostering Empathy: Nurturing Compassionate Healers through Innovative
Teaching and Insightful Assessment in Medical Education
Authors: Shrivastava Saurabh RamBihariLal , Maliny Achcia Thema , Joshi Abhishek 
Published: February 2024

Abstract:
The significance of empathy in the realm of medical education cannot be undermined, as once a student embarks on their journey to serve and heal
mankind, cultivating empathetic skills becomes an indispensable part of their training. Empathy plays a significant role in healthcare delivery in the
domains of patient outcomes and doctor-patient relationships. This article provides a brief review of empathy education and assessment techniques
in the field of medicine. Upon realizing the merits that can be attributed to empathy, it is of paramount importance that medical students must be
trained in empathy to transform them into patient-centered healthcare professionals. Only training medical students in empathy will not serve the
purpose, and we must complement the training component with assessment. In conclusion, empathy is one of the key components of
compassionate and patient-centered medical care. This calls for the need to train and assess medical students during their training period to
improve their empathetic abilities and support the process of producing competent and compassionate future medical doctors.
Prevalence and Impact of Dysmenorrhea on the Academic Performance of
Students at Medical and Health Sciences University
Authors: Mahwish Nayesha , Dube Rajani , Kar Subhranshu Sekhar , Santhosh Malavika , Kidwai Alweena , Kenneth Jewel Mary 
Published: February 2024

Introduction:
Dysmenorrhea is painful menstruation and is the most common menstrual symptom affecting adolescents. Evidence suggests that worldwide
prevalence can be high and can significantly affect academic performance through its impact on activity, absenteeism, and other aspects of
learning.

Materials and Methods:
This is a cross-sectional survey using a pre-validated questionnaire incorporating demography, menstrual history, severity, and effects on academic
performance. Female students selected by non-probability sampling of Ras al Khaimah Medical and Health Sciences University were included
(calculated sample size=249).

Results and Discussion:
A total of 252 students participated (mean age 20.14 years). The prevalence of dysmenorrhea was 80.5%. Pain was severe for 25.1% (≥7/10
score),14.7% reported severely restricted daily activity, 66% received regular treatment, and 24(11.8%) required hospitalization during the last year
due to pain. More than 50% of students missed academic sessions, 68% had trouble concentrating, 70. 4% were unable to study. 59% had an
inability to complete assignments, 58% had trouble concentrating during examinations, and 8.8% missed assessments due to dysmenorrhea. The
majority missed 1-2 days each month. Dysmenorrhea was a significant predictor of academic domains (AD) like reduced concentration, inability to
complete assignments, missing lectures, and assessments [ adjusted OR-2.25, 5.57, 4.32, 3.96] with p less than .05 in each. Moderate to severe pain
was an independent predictor of all AD compared to mild pain (score less than 3) (p=.026). Moderate to severe dysmenorrhea had a significant
negative impact on academic performance(p=.02).

Conclusion:
Dysmenorrhea is a prevalent health problem among university students and has a significant negative impact on education.
Histogram Feature Analysis of Tumor Body on Diffusion-weighted MR Imaging
in Differentiation between Granulosa Cell Tumors and Other Sex-cord Tumors
in Ovary: Comparison with Histological Results
Authors: Wu Minjie , Wang Tianping , Zhang Feiran , Wang Yida , Zhang Guofu , Shen Minhua , Zhang He 
Published: February 2024

Objective:
We aimed to differentiate granulosa cell tumors (GCT) from other ovarian sex-cord tumors (OSCs) based on feature analysis of the tumor body on
MR imaging.

Methods:
We retrospectively enrolled 27 patients with pathologically proven sex-cord tumours (14 GSTs, 8 fibromas, 4 fibrothecomas, and 1 sclerosing
stromal tumour) from our institution. All MRI examinations were performed at least one month prior to surgery. MR image features were recorded
by two radiologists with consensus readings. Histogram analysis was performed using FeAture Explorer software. The differences in histogram
parameters between GCT (38.1 ± 14.6 years) and OSC (43.7 ± 18.0 years) groups were compared. Fourteen randomly selected cellular-type
myomas who also underwent MRI in our hospital were considered as the control group. The intra-operator consistency of ADC value was
evaluated across measurements twice.

Results:
The repeatability of conventional ADC measurements on the tumor body was good. The values of ADC-mean, ADC-min, and ADC-max
significantly differed across three groups (p < 0.001). The histogram variance on DWI, histogram percentage on T2WI, and ADC min showed the
best discriminative performance in determining GCTs from other OSCs with an area under the receiver operator curve (AUC) of 0.997, 0.882, and
0.795, respectively. The histogram variance on DWI yielded a sensitivity of 92.3%, a specificity of 100%, and an accuracy of 96.6% in
discriminating GSTs from other OSCs.

Conclusion:
In the present study, feature analysis of tumor body MR imaging has helped to differentiate GST from OSC with better performance than
conventional ADC measurements.
MRI Insights in Breast Imaging
Authors: Orlando Alessia Angela Maria , Clauser Paola , Zarcaro Calogero , Ferraro Fabiola , Curatolo Calogero , Marino Maria Adele , Bartolotta Tommaso Vincenzo 
Published: February 2024

Abstract:
In the world, breast cancer is the most commonly diagnosed cancer among women. Currently, MRI is the most sensitive breast imaging method for
detecting breast cancer, although false positive rates are still an issue. To date, the accuracy of breast MRI is widely recognized across various
clinical scenarios, in particular, staging of known cancer, screening for breast cancer in high-risk women, and evaluation of response to
neoadjuvant chemotherapy. Since technical development and further clinical indications have expanded over recent years, dedicated breast
radiologists need to constantly update their knowledge and expertise to remain confident and maintain high levels of diagnostic performance in
breast MRI. This review aims to detail current and future applications of breast MRI, from technological requirements and advances to new
multiparametric and abbreviated protocols, and ultrafast imaging, as well as current and future indications.
Evaluation of Interstitial Lung Diseases with Deep Learning Method of Two
Major Computed Tomography Patterns
Authors: Kiziloğlu Hüseyin Alper , Çevik Emrah , Zengin Kenan 
Published: February 2024

Background:
Interstitial lung diseases (ILD) encompass various disorders characterized by inflammation and/or fibrosis in the lung interstitium. These
conditions produce distinct patterns in High-Resolution Computed Tomography (HRCT).

Objective:
We employ a deep learning method to diagnose the most commonly encountered patterns in ILD differentially.

Materials and Methods:
Patients were categorized into usual interstitial pneumonia (UIP), nonspecific interstitial pneumonia (NSIP), and normal lung parenchyma groups.
VGG16 and VGG19 deep learning architectures were utilized. 85% of each pattern was used as training data for the artificial intelligence model.
The models were then tasked with diagnosing the patterns in the test dataset without human intervention. Accuracy rates were calculated for both
models.

Results:
The success of the VGG16 model in the test phase was 95.02% accuracy. Using the same data, 98.05% accuracy results were obtained in the
test phase of the VGG19 model.

Conclusion:
Deep Learning models showed high accuracy in distinguishing the two most common patterns of ILD.
Pelatihan Pengelolaan Laboratorium dan Penggunaan Alat Peraga IPA bagi Guru-Guru IPA di SMP/MTs se-Kota Bandar Lampung
Authors: Rosidin Undang , Maulina Dina , Suana Wayan 
Published: February 2024

Pembelajaran IPA dan laboratorium tidak dapat dipisahkan keberadaannya secara fungsional. Guru sebagai komponen penting dalam menentukan keberhasilan pendidikan menjadi protokol dalam kegiatan pembelajaran IPA berbasis laboratorium dan pengelolaannya. Tujuan kegiatan pelatihan ini adalah untuk meningkatkan kemampuan guru dalam mengoperasikan alat peraga laboratorium, serta meningkatkan kemampuan guru terhadap teknik pengelalolaan laboratorium dan keterampilan menggunakan alat laboratorium guru. Kegiatan pelatihan ini menerapkan strategi kontekstual, yaitu mengaitkan antara teori dengan praktik yang disampaikan dengan metoda praktik terbimbing yaitu sistem pengajaran yang berorientasi pada pemecahan masalah yang dihadapi mengenai pengelolaan laboratorium. Pelaksanaan kegiatan pelatihan ini bertempat di SMP Negeri 2 Bandar Lampung, dengan subjek kegiatan pelatihan ini adalah 75 orang guru mata pelajaran IPA SMP/MTs se-Kota Bandar Lampung. Hasil kegiatan pelatihan ini menunjukan bahwa ada peningkatan pengetahuan managerial laboratorium, dimana seluruh kemampuan peseta meningkat kecuali bagi para peserta yang tidak mengikuti kegiatan pelatihan hingga akhir. Kemampuan guru dalam menggunakan alat peraga (kit) IPA sudah baik. Hasil penilaian 100% guru telah mencapai standar ketuntasan yaitu 70. Dengan demikian, kegiatan pelatihan dikatagorikan berhasil dalam meningatkan kemampuan guru IPA MTs se-Kota Bandar Lampung tata kelola laboratorium dan penggunaan perangkat/kit IPA serta mampu mengenal fungsi dan kegunaan alat dan bahan praktikum dalam menunjang pembelajaran IPA.
Diversifikasi Batik Ecoprint Menjadi Produk Aksesoris Dan Home Décor Pada UKM Betty’s Craft
Authors: Agustin Dyan , Winarto Erwin Djuni , Azizi Abrar , Hakim Luqmanul , Firdausy Khurina Nuril 
Published: February 2024

Batik ecoprint adalah batik yang memanfaatkan pewarna alami dari tanin atau zat warna daun, akar ataupun batang yang diletakan pada sehelai kain dengan direbus atau dipukul. Saat ini semakin banyak pengrajin yang menghasilkan kain dengan teknik ecoprint salah satunya UKM Betty’s Craft. UKM Betty’s Craft mengalami penurunan omset penjualan, hal ini dikarenakan motif ecoprint yang dihasilkan belum memiliki ciri khas keunggulan dan juga ragam bentuk produk akhir belum bervariasi. Dari permasalahan tersebut diperlukan solusi yaitu diversifikasi motif batik ecoprint dan ragam produk akhir menjadi produk aksesoris dan home décor. Metode yang digunakan terbagi menjadi 2 tahap, pertama diskusi dan identifikasi kebutuhan teknik kombinasi motif misalnya ecoprint dengan sibori. Kedua pelatihan pembuatan motif kombinasi dan pembuatan produk aksesoris serta home decor. Dengan kegiatan ini dihasilkan variasi produk kain dan produk jadi batik ecoprint sehingga bisa menembus pasar yang lebih luas. Dengan demikian bisa menambah pendapatan bagi UKM Betty’s Craft serta bisa membuka lapangan pekerjaan bagi masyarakat disekelilingnya.
Efficacy of the Flo App in Improving Health Literacy, Menstrual and General Health, and Well-Being in Women: Pilot Randomized Controlled Trial
Authors: Cunningham Adam C , Prentice Carley , Peven Kimberly , Wickham Aidan , Bamford Ryan , Radovic Tara , Klepchukova Anna , Fomina Maria , Cunningham Katja , Hill Sarah , Hantsoo Liisa , Payne Jennifer , Zhaunova Liudmila , Ponzo Sonia 
Published: February 2024

Background
Reproductive health literacy and menstrual health awareness play a crucial role in ensuring the health and well-being of women and people who menstruate. Further, awareness of one’s own menstrual cycle patterns and associated symptoms can help individuals identify and manage conditions of the menstrual cycle such as premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD). Digital health products, and specifically menstrual health apps, have the potential to effect positive change due to their scalability and ease of access.

Objective
The primary aim of this study was to measure the efficacy of a menstrual and reproductive health app, Flo, in improving health literacy and health and well-being outcomes in menstruating individuals with and without PMS and PMDD. Further, we explored the possibility that the use of the Flo app could positively influence feelings around reproductive health management and communication about health, menstrual cycle stigma, unplanned pregnancies, quality of life, work productivity, absenteeism, and body image.

Methods
We conducted 2 pilot, 3-month, unblinded, 2-armed, remote randomized controlled trials on the effects of using the Flo app in a sample of US-based (1) individuals who track their cycles (n=321) or (2) individuals who track their cycles and are affected by PMS or PMDD (n=117).

Results
The findings revealed significant improvements at the end of the study period compared to baseline for our primary outcomes of health literacy (cycle tracking: D̄=1.11; t311=5.73, P<.001; PMS or PMDD: D̄=1.20; t115=3.76, P<.001) and menstrual health awareness (D̄=3.97; t311=7.71, P<.001), health and well-being (D̄=3.44; t311=5.94, P<.001), and PMS or PMDD symptoms burden (D̄=–7.08; t115=–5.44, P<.001). Improvements were also observed for our secondary outcomes of feelings of control and management over health (D̄=1.01; t311=5.08, P<.001), communication about health (D̄=0.93; t311=2.41, P=.002), menstrual cycle stigma (D̄=–0.61; t311=–2.73, P=.007), and fear of unplanned pregnancies (D̄=–0.22; t311=–2.11, P=.04) for those who track their cycles, as well as absenteeism from work and education due to PMS or PMDD (D̄=–1.67; t144=–2.49, P=.01).

Conclusions
These pilot randomized controlled trials demonstrate that the use of the Flo app improves menstrual health literacy and awareness, general health and well-being, and PMS or PMDD symptom burden. Considering the widespread use and affordability of the Flo app, these findings show promise for filling important gaps in current health care provisioning such as improving menstrual knowledge and health.

Trial Registration
OSF Registries osf.io/pcgw7; https://osf.io/pcgw7 ; OSF Registries osf.io/ry8vq; https://osf.io/ry8vq
Eficacia y equidad espacial en servicios de educación y salud. Método y evidencias para Guadalajara
Authors: Rodríguez López Alondra , Alegría Olazábal Tito Alejandro 
Published: February 2024

La proximidad de los servicios es crucial para reducir las desigualdades sociales. Aquí se estima la cobertura espacial de escuelas/hospitales; también se analiza si las variaciones en la cantidad de servicio recibido se asocian con el nivel socioeconómico de los vecindarios. Partimos del supuesto de que la geografía del servicio es ineficaz e inequitativa. Con el cálculo de buffers, estadísticas de zona y regresiones lineales, se encontró que el servicio de bachilleratos y hospitales está centralizado, no así la distribución de primarias/secundarias; además, los grupos desfavorecidos reciben menor oferta de servicios, pero esto débilmente se relaciona con el factor socioeconómico.
Evaluation of Pregnant Knowledge and Adherence Regarding Supplemental Iron, Folic acid, Calcium, and Vitamins During Pregnancy
Authors: Karim Walaa A. , Rabea Ihsan S. , Abdulwahid Hameeda H. 
Published: February 2024

Objectives: The aim of the present study is to evaluate the knowledge as well as the rate of adherence to supplement medications.
Methods: The cross-sectional study was carried out at a teaching hospital for obstetrics and gynecology in Karbala with 100 pregnant women at the second trimester, data were collected using two questionnaires, one about knowledge and other about adherence to micronutrient supplementation, laboratory tests were used to determine the levels of Hemoglobin and plasma level of calcium, and vitamin D.
Results: the overall adherence rate to supplement medication among pregnant women was low in spite of good knowledge score. Biochemical laboratory results showed more than half of participants were found to have haemoglobin
Less than normal level. Most of participant confirmed to have deficiency of plasma 25-Hydroxy-vitaminD, and more than two third of them have normal calcium level.
Conclusion: the present study revealed that most pregnant women have a poor adherence to micronutrient supplementation, therefore there is a need for interventional strategies to optimize adherence.
Sinergi Paramassa: Implementation of the Social Values of the Meugang Tradition into Digital Music Composition
Authors: Gusmanto Rico , Denada Berlian 
Published: February 2024

The Meugang tradition as Acehnese local wisdom is an activity that has a togetherness. This togetherness is a social value that creates a harmonious society in the midst of the globalization era. This is something interesting to implement in the form of music compositions. The aim of this research is to create a music that implement social values in the Meugang tradition through the use of a Digital Audio Workstation. The method used is an artistic research method which consists of 1) the formulation of ideas; 2) determine the work; 3) express ideas; 4) and performances. The result of this research is music entitled "Sinergi Paramassa". This music consists of two parts that represent Meugang activities and values asah, asih, and asuh. It is hoped that this research can be an answer to the challenges of music development in the digital era in terms of the novelty of the music content sourced from local Indonesian wisdom.
Harmonization of higher education and student management by integrating information technology
Authors: Yang Ling 
Published: February 2024

Abstract
In recent years, higher education management has been improving, but the coordinated development of the overall educational management and student management system of colleges and universities still needs to be further improved and enhanced. This paper uses data envelopment analysis and data fusion technology to establish DEA fusion algorithm and DEA-Malmquist index method to evaluate and analyze students’ learning efficiency in colleges and universities. The results indicated that the average degree of perfection of online teaching management in higher education is low, 86.2%. Students’ overall satisfaction with this is also expected at 56.2%. There is a need to strengthen management and improve classroom interactivity and innovation, to enhance the quality and attractiveness of courses, and to avoid excessive fragmentation. In addition to the existing problems, the results achieved include more accessible access to learning resources, with a percentage of 88.6%. The algorithm of this paper is used to study the efficiency of higher education and student learning, and to provide a more comprehensive and objective approach to the development of the quality of higher education and student management for the later development of higher education.
Exploring New Directions in Higher Education Aided by Artificial Intelligence Technology
Authors: Wang Junqiao 
Published: February 2024

Abstract
This paper’s objective optimization problem belongs to the encoding problem of real numbers, and the classical particle swarm optimization algorithm is chosen. The establishment of intelligent learning model was finally completed through the assumption of model components, initial model establishment, model cycle evaluation and validation. First, after the implementation of the E-GPPE-C education model, the test was conducted on the educated people, and the AI literacy questionnaire was also distributed to the students before and after the implementation of the model education. Second, a statistical analysis explores which technologies will most likely be applied to higher education. Finally, the variability of higher education subject relations under the influence of AI and related ethical issues were explored. The results show that the highest score on the students’ final test was 96. 20 students scored more than 80 points, indicating that half of the students had a solid grasp of the knowledge and applications related to the E-GPPE-C model, and that there was a vast difference between the degree of AI knowledge and skill mastery before and after the implementation of education. Natural language understanding, computer vision, and biometrics are the three technologies most suitable for application in higher education.