bluuebunny/crossref_metadata_2025 huggingface dataset:
СИСТЕМИ ПРОГРАМНО-КОНФІГУРОВАНОГО РАДІО ЯК ОСНОВА РОЗВИТКУ ПЕЛЕНГАЦІЙНИХ РАДІОТЕХНІЧНИХ СИСТЕМ НАСТУПНОГО ПОКОЛІННЯ
Authors: Полікаровських Олексій , Бойко Юлій , Ткачук Віталій , Авдєєв Віктор , Свістунов Олексій
Published: May 2022

Сучасна тенденція проникнення програмно-конфігурованого радіо (SDR - Software Defined Radio) у науку, виробництво визначається появою на ринку доступних та багатофункціональних програмно-апаратних рішень. Аналіз досвіду розробки сучасних радіотехнічних комплексів дозволяє говорити про виникнення нової парадигми в галузі телекомунікацій та радіозв'язку, пов'язаної з напрямком SDR. З точки зору розробника сучасної радіоапаратури напрямок SDR є багатовекторним і охоплює наступні сфери застосування: радіоприймальні та радіопередавальні пристрої, радіолокація і пеленгація, системи електричного зв'язку. Метою роботи є історичний огляд та огляд сучасних тенденцій у галузі створення радіотехнічних комплексів на основі систем SDR. Для цього у роботі аналізуються особливості стандартизації та архітектура радіостанції SDR, сучасні тенденції використання SDR, зарубіжний досвід використання SDR, еволюція радіостанцій SDR, структура апаратної частини радіоприймача RTL-SDR, особливості реалізації приймача SDR у спеціалізованому програмному забезпеченні (СПО).
МОДЕЛЮВАННЯ ПРОЦЕСУ ПІДТРИМКИ ПРИЙНЯТТЯ РІШЕНЬ ЩОДО МОЖЛИВОСТІ УКЛАДАННЯ ДОГОВОРУ ПРО НАДАННЯ ТЕРАПЕВТИЧНИХ ПОСЛУГ
Authors: Гнатчук Єлизавета
Published: May 2022

Наразі в Україні існує потреба в проектуванні та розробленні системи підтримки прийняття рішень (СППР) щодо можливості укладання договору про надання терапевтичних послуг (з врахуванням коректності або некоректності договору з юридичної точки зору), яка може значно підвищити ефективність роботи терапевта та страхової медицини, а також захистити як пацієнтів, так і лікарів. Для проектування такої СППР спочатку слід розробити теоретичне підгрунтя, а саме провести моделювання процесу підтримки прийняття рішень щодо можливості укладання договору про надання терапевтичних послуг. У статті розроблено теоретико-множинну модель договору про надання терапевтичних послуг, яка ґрунтується на істотиних умовах договору, що є обов’язковими з точки зору цивільно-правових підстав. Крім цього, проведено моделювання процесу підтримки прийняття рішень щодо можливості укладання договору про надання терапевтичних послуг. Розроблена модель процесу підтримки прийняття рішень щодо можливості укладання договору про надання терапевтичних послуг є теоретичним підґрунтям для розроблення методів та проектування СППР щодо можливості укладання договору про надання терапевтичних послуг.
REKAYASA PROSES DISTILASI EKSTRAKTIF PADA PEMBUATAN PELARUT BERBASIS HIDROKARBON DENGAN MENGGUNAKAN ENTRAINER SULFOLANA
Authors: Prasetiawan Haniif , Kusumaningtyas Ratna Dewi , Triwibowo Bayu , Hartanto Dhoni , Al Ghifari Muhammad Fikri , Karimah Syifa
Published: May 2022

Pelarut atau solvent merupakan salah satu komponen penting dalam proses kimia pada industri kimia. Salah satu jenis pelarut yang sering digunakan pada industri cat dan pelapis yaitu pelarut berbasis hidrokarbon yang terdiri dari campuran cairan kompleks yang beragam dan mengandung unsur alifatik, alisiklik dan aromatik (C5-C8). Aromatik hidrokarbon merupakan polutan lingkungan yang terkenal bersifat toksik, karsinogenik dan mutagenik sehingga dibutuhkan pelarut berbasis hidrokarbon dengan kandungan aromatik dibawah 1%. Metode pemisahan yang tepat untuk memisahkan komponen aromatik dan nonaromatik yang memiliki titik didih berdekatan adalah distilasi ekstraktif dengan entrainer sulfolana. Pada penelitian ini, sistem distilasi dengan entrainer sulfolana dijalankan menggunakan process simulation software Aspen Plus V.10 dengan tujuan untuk mengetahui pengaruh jumlah sulfolana, feed stage dan jumlah stage terhadap sifat fisis pelarut berbasis hidrokarbon serta analisis energi dan ekonominya. Simulasi ini difokuskan pada variasi rasio sulfolana:crude feed ( 7:1, 7,5:1, 8:1, 8,5:1), variasi feed stage (stage ke-10 sampai ke-35) dan variasi jumlah stage (70,75,80). Hasil penelitian didapatkan kondisi optimum yaitu menggunakan rasio sulfolana:crude feed  8,5:1, feed stage ke-25 dan jumlah stage 80.
PELATIHAN DAUR ULANG SAMPAH PLASTIK UNTUK MENGOPTIMALKAN KEGIATAN EKSTRAKURIKULER MAHASISWA PROGRAM STUDI BIOLOGI
Authors: Zebua Lisye Iriana
Published: May 2022

Trash is a wasted or discarded material  from the source of human activities and natural processes that do not have economic value. The plastic waste is the largest number of waste from human because many people are using plastic for everyday life. Everyone, when plastic shopping will definitely need to bring groceries. If the plastic is not used normally people would throw it into the trash, to the river, to the ground, or even burned directly. Until now, the students of Biology not thought to try the plastic waste recycling. This is due to limited knowledge and skills of the students in Department of Biology on recycling of plastic waste. Therefore, the training and practice of recycling plastic waste needs to be done as one of concern for students from the Department of Biology to supports the government programs paid on plastic bags. The activity methods used are observation and practice in the field by collecting and utilizing waste plastic household scale (eg: plastic refill fragrances, clothing, soap, and dishwashing soap) that exist in the environment. The students will create a straight pattern bag with a variety of innovations models. The bag can serve as a shopping cart bag with a variety of sizes. The end result of this activity is the creation of product innovation models of multi-functional shopping cart bags are environmentally friendly. In addition, with the end of the training activity, the knowledge and care about environmental of the students are growing more higher. Keywords: training, recycling, plastic waste, students of Department of Biology
PENERAPAN MODEL DIRECT INSTRUCTION DALAM PEMBELAJARAN OLAHRAGA PATANQUE
Authors: Ita Saharuddin , Wiwit Wiwit , Putra M. FP.
Published: May 2022

Petanque is new sport, specially in Papua-Indonesia. Because of new sport so many student can not right play of petanque sport. Giving training with model of Direct Instruction (DI) can be solution to solve the problem in field. Sport action was taked as method of service. The find out of the service was (1) training with model of direct instruction increasing learning achievement student of petanque sport, (2) training with model of direct instruction increasing learning achievement university student of petanque sport.Keywords: direct instruction, petanque sport, Papua
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Authors: Jurnal Pengelola
Published: May 2022

Cover Jurnal
DEVELOPMENT OF BIOLOGY MODULE BASED ON DISCOVERY LEARNING TO INCREASE INTEREST AND LEARNING RESULTS CLASS X STUDENTS ON PLANT MATERIALS
Authors: Suryandari Ririn
Published: May 2022

This research is a research and development (Research & Development) which aims to find out how to develop a discovery learning-based biology learning module to increase the interest and learning outcomes of students class X on plant material at YPK Bethel Aimas High School, Sorong Regency.The data analysis technique used descriptive presentation to determine the feasibility of the module. The results of there search show that: (1) The interest of students in learning biology increased after using the biology module, before using the module is 77, 94% after using the module increased to 90.81%; (2) There is anincrease in biology learning outcomes after modules as indicated by the n-Gain value in RPP 1 of 0.52, RPP 2 of 0.63, and RPP 3 of 0.69.
THE DEVELOPMENT OF PHYSICS E-MODULES BASED ON PJBL STEM ON VECTOR ANALYSIS MATERIAL ON PARABOLIC MOTION
Authors: Kurniawan Victoria Dian Pratami , Bungkang Yusuf , Lumbu Albert
Published: May 2022

This study aims to determine the feasibility of developing PjBL STEM-based Physics e-modules and improving student learning outcomes using PjBL STEM-based Physics e-modules on vector analysis materials on parabolic motion. The research method used is R&D (Research and Development). The research sample consisted of 24 students. The results showed that the feasibility of the PjBL STEM-based Physics e-module on vector analysis material on parabolic motion obtained an average percentage of 92% with a very suitable category for use as a teaching material, and improving student learning outcomes with the n-Gain test obtained an average of 0 .77 with high category
ANALYSIS OF ANTIOXIDANT ACTIVITY OF LIDAH MERTUA LEAVES (Sansevieria trifasciatalauretii) USING DPPH METHOD
Authors: I M Dwi Cahya Putra , W Bogoriani N
Published: May 2022

Lidah mertua plant  has the potential as a natural antioxidant and the antioxidant activity of a plant depends on the number of active compounds extracted. This study aims to determine the yield, total phenol content, total flavonoid content, and IC50 value of lidahmertua leaf extract macerated with ethanol, ethyl acetate, and n-hexane as solvents, and to determine the compounds contained in the lidahmertua leaf extract which have activity antioxidants. The results of the phytochemical test of the lidahmertua leaf extract showed positive results containing polyphenolic compounds, flavonoids, saponins, alkaloids, and steroids. The maceration yield of each solvent was 12.13%, 10.15% and 8.11%, respectively. While the measurement results of the total phenol content of each solvent were 6.96; 3.67; and 1.94 mg GAE/g. The results of the measurement of the flavonoid content of each solvent were 5.82; 3.28; and 1.71 mg QE/g. The IC50 values for each solvent were 162.135 mg/L, 184.561 mg/L and 206.265 mg/L. The extract which has the highest total phenol content, total flavonoid content, and antioxidant activity is in ethanol solvent.
THE DEVELOPMENT OF E-MODULES BASED ON THE SCIENTIFIC APPROACH TO THE ADJUSTMENT OF LIVING CREATURES TO THEIR ENVIRONMENT
Authors: Sunaryatin Sunaryatin , Siregar Tiurlina , Wahyudi Irfan
Published: May 2022

This study aims to find out how to create a science e-module, develop a science e-module, the feasibility of developing a science e-module, and improve student learning outcomes by using a science e-module based on a scientific approach to the adaptation of living things to their environment. Research Methods Research and Development. The research sample was carried out in class V SD YPKP 2 Sentani with a total of 25 students. The results showed that: 1) The steps of making e-modules as teaching materials through seven components of e-modules, namely the formulation of teaching objectives, instructions for using e-modules, activity sheets, student worksheets, evaluation sheets, navigation menus and other features. interactive features. 2) The feasibility of the science module based on a scientific approach on the adaptation of living things to their environment which consists of material validation components, media validation, teacher responses from YPKP 2 Sentani Elementary School teachers, and YPKP 2 Sentani Elementary School students' responses are very good, with an average module eligibility IPA is 92.82% with a very suitable category to be used as teaching material. The increase in student learning outcomes with the n-Gain test obtained an average of 0.6 in the medium category.
ECG Classification Using Combination of Linear and Non-Linear Features with Neural Network
Authors: Biloborodova Tetiana , Skarga-Bandurova Inna , Skarha-Bandurov Illia , Yevsieieva Yelyzaveta , Biloborodov Oleh
Published: May 2022

In this paper, we present an approach to improve the accuracy and reliability of ECG classification. The proposed method combines features analysis of linear and non-linear ECG dynamics. Non-linear features are represented by complexity measures of assessment of ordinal network non-stationarity. We describe the basic concept of ECG partitioning and provide an experiment on PQRST complex data. The results demonstrate that the proposed technique effectively detects abnormalities via automatic feature extraction and improves the state-of-the-art detection performance on one of the standard collections of heartbeat signals, the ECG5000 dataset.
Dataset Comparison Tool: Utility and Privacy
Authors: Coutinho-Almeida João , Cruz-Correia Ricardo João , Rodrigues Pedro Pereira
Published: May 2022

Synthetic data has been more and more used in the last few years. While its applications are various, measuring its utility and privacy is seldom an easy task. Since there are different methods of evaluating these issues, which are dependent on data types, use cases and purpose, a generic method for evaluating utility and privacy does not exist at the moment. So, we introduced a compilation of the most recent methods for evaluating privacy and utility into a single executable in order to create a report of the similarities and potential privacy breaches between two datasets, whether it is related to synthetic or not. We catalogued 24 different methods, from qualitative to quantitative, column-wise or table-wise evaluations. We hope this resource can help scientists and industries get a better grasp of the synthetic data they have and produce more easily and a better basis to create a new, more broad method for evaluating dataset similarities.
AP-HP Health Data Space (AHDS) to the Test of the Covid-19 Pandemic
Authors: Daniel Christel ,   AP-HP Covid CDW Initiative, Paris Nicolas , Pierre Olivier , Griffon Nicolas , Breant Stéphane , Orlova Nina , Serre Patricia , Leprovost Damien , Denglos Stéphane , Mouchet Alexandre , Dubiel Julien , Gozlan Rafael , Chatellier Gilles , Bey Romain , Frank Marie , Hassen-Khodja Claire , Mamzer Marie-France , Hilka Martin
Published: May 2022

Sharing observational and interventional health data within a common data space enables university hospitals to leverage such data for biomedical discovery and moving towards a learning health system. Objective: To describe the AP-HP Health Data Space (AHDS) and the IT services supporting piloting, research, innovation and patient care. Methods: Built on three pillars – governance and ethics, technology and valorization – the AHDS and its major component, the Clinical Data Warehouse (CDW) have been developed since 2015. Results: The AP-HP CDW has been made available at scale to AP-HP both healthcare professionals and public or private partners in January 2017. Supported by an institutional secured and high-performance cloud and an ecosystem of tools, mostly open source, the AHDS integrates a large amount of massive healthcare data collected during care and research activities. As of December 2021, the AHDS operates the electronic data capture for almost +840 clinical trials sponsored by AP-HP, the CDW is enabling the processing of health data from more than 11 million patients and generated +200 secondary data marts from IRB authorized research projects. During the Covid-19 pandemic, AHDS has had to evolve quickly to support administrative professionals and caregivers heavily involved in the reorganization of both patient care and biomedical research. Conclusion: The AP-HP Data Space is a key facilitator for data-driven evidence generation and making the health system more efficient and personalized.
Attitudes and Acceptance Towards Artificial Intelligence in Medical Care
Authors: Holzner Dana , Apfelbacher Timo , Rödle Wolfgang , Schüttler Christina , Prokosch Hans-Ulrich , Mikolajczyk Rafael , Negash Sarah , Kartschmit Nadja , Manuilova Iryna , Buch Charlotte , Gundlack Jana , Christoph Jan
Published: May 2022

Background: Artificial intelligence (AI) in medicine is a very topical issue. As far as the attitudes and perspectives of the different stakeholders in healthcare are concerned, there is still much to be explored. Objective: Our aim was to determine attitudes and aspects towards acceptance of AI applications from the perspective of physicians in university hospitals. Methods: We conducted individual exploratory expert interviews. Low fidelity mockups were used to show interviewees potential application areas of AI in clinical care. Results: In principle, physicians are open to the use of AI in medical care. However, they are critical of some aspects such as data protection or the lack of explainability of the systems. Conclusion: Although some trends in attitudes e.g., on the challenges or benefits of using AI became clear, it is necessary to conduct further research as intended by the subsequent PEAK project.
Supporting AI-Explainability by Analyzing Feature Subsets in a Machine Learning Model
Authors: Plagwitz Lucas , Brenner Alexander , Fujarski Michael , Varghese Julian
Published: May 2022

Machine learning algorithms become increasingly prevalent in the field of medicine, as they offer the ability to recognize patterns in complex medical data. Especially in this sensitive area, the active usage of a mostly black box is a controversial topic. We aim to highlight how an aggregated and systematic feature analysis of such models can be beneficial in the medical context. For this reason, we introduce a grouped version of the permutation importance analysis for evaluating the influence of entire feature subsets in a machine learning model. In this way, expert-defined subgroups can be evaluated in the decision-making process. Based on these results, new hypotheses can be formulated and examined.
Extraction of Tumor Response Criteria in Semi-Structured Imaging Report
Authors: Pohyer Valentin , Baudoin David , Fournier Laure , Rance Bastien
Published: May 2022

In this study, we extracted information from 6,376 french CT scan semi-structured text reports evaluating the cancer treatment response using the RECIST methodology. We evaluated the performance against manual annotation of 100 reports and measured the evolution of the presence of information over time. The results show high performances of the extraction as well as trends.
Making EHRs Trustable: A Quality Analysis of EHR-Derived Datasets for COVID-19 Research
Authors: Pedrera-Jimenez Miguel , Garcia-Barrio Noelia , Rubio-Mayo Paula , Maestro Guillermo , Lalueza Antonio , Garcia-Reyne Ana , Zamorro María José , Pons Alejandra , Sanchez-Martin María Jesús , Cruz-Rojo Jaime , Quiros Víctor , Aguado José María , Cruz-Bermudez Juan Luis , Bernal José Luis , Merson Laura , Lumbreras Carlos , Serrano Pablo
Published: May 2022

One approach to verifying the quality of research data obtained from EHRs is auditing how complete and correct the data are in comparison with those collected by manual and controlled methods. This study analyzed data quality of an EHR-derived dataset for COVID-19 research, obtained during the pandemic at Hospital Universitario 12 de Octubre. Data were extracted from EHRs and a manually collected research database, and then transformed into the ISARIC-WHO COVID-19 CRF model. Subsequently, a data analysis was performed, comparing both sources through this convergence model. More concepts and records were obtained from EHRs, and PPV (95% CI) was above 85% in most sections. In future studies, a more detailed analysis of data quality will be carried out.
Multi-Dimensional Laboratory Test Score as a Proxy for Health
Authors: Ezra Bar H. , Havaldar Shreyas , Glicksberg Benjamin , Rappoport Nadav
Published: May 2022

The standard of care for a physician to review laboratory tests results is to weigh each individual laboratory test result and compare it to against a standard reference range. Such a method of scanning can lead to missing high-level information. Different methods have tried to overcome a part of the problem by creating new types of reference values. This research proposes looking at test scores in a higher dimension space. And using machine learning approach, determine whether a subject has abnormal tests result that, according to current practice, would be defined as valid – and thus indicating a possible disease or illness. To determine health status, we look both at a disease-specific level and disease-independent level, while looking at several different outcomes.
Design Considerations for the Use of Patient-Generated Health Data in the Electronic Medical Records
Authors: Blondon Katherine , Ehrler Frederic
Published: May 2022

Patient-generated health data (PGHD) is of growing interest to physicians, particularly if they are integrated in the electronic medical record (EMR). Concerns about how to manage vast amounts of PGHD and potential liability issues have limited their use. Based on interviews with specialists, we present types of PGHD, workflow processes and needs. We then discuss consideration for how to manage PGHD with approaches for analyses to detect abnormal results, and present implications for alert systems and visualization requirements in multi-patient views.
Temporal Medical Knowledge Representation Using Ontologies
Authors: Hilbey Jacques , Aimé Xavier , Charlet Jean
Published: May 2022

Representing temporal information is a recurrent problem for biomedical ontologies. We propose a foundational ontology that combines the so-called three-dimensional and four-dimensional approaches in order to be able to track changes in an individual and to trace his or her medical history. This requires, on the one hand, associating with any representation of an individual the representation of his or her life course and, on the other hand, distinguishing the properties that characterize this individual from those that characterize his or her life course.
Using Big Data to Identify Impact of Asthma on Mortality in Patients with COVID-19
Authors: Lyu Jinyan , Cui Wanting , Finkelstein Joseph
Published: May 2022

The goal of this paper was to assess if mortality in COVID-19 positive patients is affected by a history of asthma in anamnesis. A total of 48,640 COVID-19 positive patients were included in our analysis. A propensity score matching was carried out to match each asthma patient with two patients without history of chronic respiratory diseases in one stratum. Matching was based on age, comorbidity score, and gender. Conditional logistics regression was used to compute within each strata. There were 5,557 strata in this model. We included asthma, ethnicity, race, and BMI as risk factors. The results showed that the presence of asthma in anamnesis is a statistically significant protective factor from mortality in COVID-19 positive patients.
FAIRifying a Quality Registry Using OMOP CDM: Challenges and Solutions
Authors: Puttmann Daniel , De Keizer Nicolette , Cornet Ronald , Van Der Zwan Eric , Bakhshi-Raiez Ferishta
Published: May 2022

The need for health data to be internationally Findable, Accessible, Interoperable and Reusable (FAIR) and thereby support integrative analysis with other datasets has become crystal clear in the ongoing pandemic. The Dutch National Intensive Care Evaluation (NICE) quality registry adopted the Observational Medical Outcomes Partnership Common Database Model (OMOP CDM) to achieve a FAIR database. In the process of adopting the OMOP CDM, many modeling, technical, and communication challenges needed to be solved. Through communication with the OMOP CDM implementation community, previously done research and trial-and-error we found solutions that we believe can help other healthcare institutions, especially ICU quality registries, FAIRify their databases.
A Conceptual Framework for Representing Events Under Public Health Surveillance
Authors: Okhmatovskaia Anya , Shen Yannan , Ganser Iris , Collier Nigel , King Nicholas B. , Meng Zaiqiao , Buckeridge David L.
Published: May 2022

Information integration across multiple event-based surveillance (EBS) systems has been shown to improve global disease surveillance in experimental settings. In practice, however, integration does not occur due to the lack of a common conceptual framework for encoding data within EBS systems. We aim to address this gap by proposing a candidate conceptual framework for representing events and related concepts in the domain of public health surveillance.
Large-File Raw Data Synchronization for openBIS Research Repositories
Authors: Dudchenko Aleksei , Ringwald Friedemann , Czernilofsky Felix , Dietrich Sascha , Knaup Petra , Ganzinger Matthias
Published: May 2022

In a systems medicine research consortium, openBIS is used as a research data repository. To facilitate efficient upload of large files, openBIS is complemented by a Nextcloud data cloud system. Using a Nextcloud client, raw mass spectrometry data is automatically imported into the repository in the background, enabling comprehensive data provenance.
Causal Associations Among Diseases and Imaging Findings in Radiology Reports
Authors: Sebro Ronnie , Kahn Jr. Charles E.
Published: May 2022

This study explored the ability to identify causal relationships between diseases and imaging findings from their co-occurrences in radiology reports. A natural language processing (NLP) system with negative-expression filtering detected positive mentions of 16,912 disorders, interventions, and imaging findings in 1,702,462 consecutive radiology reports; the 55,564 causal relations defined by the Radiology Gamuts Ontology (RGO) served as reference standard. Conditions were considered to co-occur if they were present in reports from the same patient. The ϕ and κ statistics both achieved AUC0.70, P<0.001 in identifying causal relationships from pairwise co-occurrence data. Analysis of radiology reports can identify a large proportion of known causal associations among diseases and imaging findings. Automated approaches hold promise to identify causal relationships among diseases and imaging findings from their co-occurrence in text-based radiology reports.
An Interactive Interface for Displaying Recommendations on Emergency Phone Triage in Pediatrics
Authors: Durchon Claire , Vanderlan Stephi , Jegard Alice , Saram Hasini , Falchi Marina , Campeotto Florence , Dupic Laurent , Burgun Anita , Vivien Benoît , Tsopra Rosy
Published: May 2022

Emergency phone triage aims at identifying quickly patients with critical emergencies. Patient triage is not an easy task, especially in situations involving children, mostly due to the lack of training and the lack of clinical guidelines for children. To overcome these issues, we aim at designing and assessing an interactive interface for displaying recommendations on emergency phone triage in pediatrics. Four medical students formalized local guidelines written by the SAMU of Paris, into a decision tree and designed an interface according to usability principles. The navigation within the interface was designed to allow the identification of critical emergencies at the beginning of the decision process, and thus ensuring a quick response in case of critical emergencies. The interface was assessed by 10 medical doctors: they appreciated the ergonomics (e.g., intuitive colors), and found easy to navigate through the interface. Nine of them would like to use this interface during phone call triage. In the future, this interface will be improved and implemented in emergency call centers.
Clinical Decision Support System for PIM in Elderly Patients: Implementation and Initial Evaluation in Ambulatory Care
Authors: Frutos Eliana , Kakazu Martin , Tajerian Matias , Gaiera Alejandro , Rubin Luciana , Otero Carlos , Luna Daniel
Published: May 2022

The high prevalence of PIMs in elderly is a major healthcare concern and indicates the need for medication monitoring systems. Most PIM CDSS have shown positive effects respecting PIM prescription but these results were more consistently in hospital settings compared with ambulatory care. We describe the post-implementation evaluation of a PIM CDSS for general practitioners (GP) in the ambulatory setting and explore GP interactions with the PIM alerts. The CDSS generated 3218 unique alerts and involved 2863 elderly patients. Benzodiazepines was the drug with the most alerts triggered. Only 129 (4 %) were opened by GP during patient appointments. We need to develop an understanding of how alerts should be designed and display information to support the workflow of general practitioners. Pos-implementation evaluations are the key of CDSS improvements.
National Integration Components Challenge the Epic Implementation in Central Norway
Authors: Ellingsen Gunnar , Hertzum Morten , Christensen Bente , Wynn Rolf
Published: May 2022

Electronic health record (EHR) suites cover a broad range of cross-sectoral use scenarios. Thereby, they streamline information flows but also require that healthcare professionals with diverse responsibilities must adapt to one and the same system. In the region of Central Norway, the EHR suite from Epic is being implemented at hospitals as well as in municipal healthcare. However, the 64 municipalities in the region are increasingly exploring the option of bypassing Epic by supplementing their existing systems with national integration components. These components provide integration and data exchange across systems for selected healthcare information. We discuss whether they are a viable alternative to Epic. The three components are the summary care record, the shared medication list, and the national welfare technology hub.
Assessment of Health Service Quality Through Electronic Health Record – A Scoping Review
Authors: von Gerich Hanna , Peltonen Laura-Maria
Published: May 2022

The World Health Organization defines, that high quality health services should be effective, safe, people-centered, timely, equitable, integrated, and effective. This requires systematic quality assessment. The aim of this scoping review was to explore how electronic health records (EHRs) have been used to assess quality of health services using the WHO criteria. A total of 4247 records were obtained whereof 8 studies were included in the review. Research showed that EHRs were used to evaluate safety, performance and care processes. EHRs were regarded as an applicable real-world data source, highlighting the importance of consistency and standardised terminologies. Use of EHR data is limited to its representation of the real world and current evaluation systems have limited quality criteria, diverse definitions and they use only structured data. Future research should explore possibilities of natural language processing methods and include narrative EHR information for a more a comprehensive view of service quality assessment.
Exploring the Digital Divide as a Barrier to Use of a Personal Health Record in the Elderly
Authors: Frutos Eliana , Descalzo Juan , Colussi Giuliana , Rapisarda Romina , Plazzotta Fernando , Luna Daniel
Published: May 2022

The digital divide can hinder the ability of elderly patients to fully benefit from PHRs. They are “digital immigrants”, not having the life-long exposure to technology as younger generations, as well as physical and cognitive disabilities. The aim of this study was to explore the digital divide as a barrier for the use of a PHR in older adults (> 69 years of age) and describe the use of a PHR in an elderly population in Argentina. We conducted a cross sectional study which included older adults who attended the Coronavirus vaccination campaign in 2021. Data were collected through a survey encompassing digital divide factors and use of the PHR. A total of 128 participants agreed to complete the survey, 60.15% reported using the PHR. We found a statistically significant correlation of education level, having a personal computer and internet access with PHR use. Concerning PHR users, 45.45% reported needing assistance to use it. Although the elderly population represents a large portion of patients, there is not enough research done on their use experience using eHealth solutions. There is pending work in the eHealth field to integrate these elders into current PHRs and help them enjoy their benefits.
MIMIC-IV as a Clinical Data Schema
Authors: Giesa Niklas , Heeren Patrick , Klopfenstein Sophie , Flint Anne , Agha-Mir-Salim Louis , Poncette Akira , Balzer Felix , Boie Sebastian
Published: May 2022

Routinely collected electronic health records (EHR) in clinical information systems (CIS) are often heterogeneous, have inconsistent data formats and lack of documentation. We use the well-known open-source database schema of MIMIC-IV to address this issue aiming to support collaborative secondary analysis. Over 154 million data records from a German ICU have already been mapped and inserted into the schema successfully. However, discrepancies between the German and US health systems as well as specifics in our clinical source data hinder the direct translation to MIMIC. Evaluating and improving mapping completeness is part of the ongoing research.
Wake-up Stroke Outcome Prediction by Interpretable Decision Tree Model
Authors: Ajčević Miloš , Miladinović Aleksandar , Furlanis Giovanni , Buoite Stella Alex , Naccarato Marcello , Caruso Paola , Manganotti Paolo , Accardo Agostino
Published: May 2022

Outcome prediction in wake-up ischemic stroke (WUS) is important for guiding treatment strategies, in order to improve recovery and minimize disability. We aimed at producing an interpretable model to predict a good outcome (NIHSS 7-day<5) in thrombolysis treated WUS patients by using Classification and Regression Tree (CART) method. The study encompassed 104 WUS patients and we used a dataset consisting of demographic, clinical and neuroimaging features. The model was produced by CART with Gini split criterion and evaluated by using 5-fold cross-validation. The produced decision tree model was based on NIHSS at admission, ischemic core volume and age features. The predictive accuracy of model was 86.5% and the AUC-ROC was 0.88. In conclusion, in this preliminary study we identified interpretable model based on clinical and neuroimaging features to predict clinical outcome in thrombolysis treated wake-up stroke patients.
Over 89% Adoption Rate of the Nationwide Online Patient Portal in Finland
Authors: Jormanainen Vesa
Published: May 2022

Among 1,650 persons in an internet panel survey in October 2020 in Finland, over 89% reported use of the nationwide My Kanta online patient portal. Only 1.5% of the respondents did not know the service. Compared with non-users, among My Kanta users there were more females, less living in countryside, household net income was higher, and more reported independent use of online services. My Kanta use increased by poorly self-rated health status, increasing number of reported prescribed medicines, long-term diseases and physician visits during the six previous months.
Understanding Public Priorities and Perceptions of the Use of Linked Healthcare Data in South East England
Authors: Ford Elizabeth , Stanley Kathryn , Rees-Roberts Melanie , Giles Sarah , Goddard Katie , Armes Jo
Published: May 2022

The counties of Kent, Surrey and Sussex (KSS) in South East England are creating anonymized, linked databases of healthcare records for audit, service planning and research for the first time. We consulted with 79 citizens from KSS in 5 deliberative focus groups, asking about perceived benefits and concerns regarding these new data assets. Participants hoped the linked datasets could be used for joining up care and information, improving efficiency, and improving healthcare provision, but were concerned about missing and inaccurate data, data breaches and hacking, use of data by profit-making organisations, and stigma and discrimination. Findings will be used to underpin governance and engagement strategies for integrated datasets in KSS.
Why Do People Use Online Lab Results and What Do They Look For: A Qualitative Study
Authors: Monkman Helen , Griffith Janessa , Macdonald Leah , Joseph Amanda L. , Lesselroth Blake
Published: May 2022

Laboratory (lab) test results are increasingly available online for patient review. However, there is a dearth of research with respect to users’ information needs, goals, and information processing strategies. In this exploratory qualitative study, we interviewed a sample of (N = 25) online lab results users to understand their objectives and search targets. We transcribed their responses and used affinity diagramming to identify themes in their responses. Our analysis identified six reasons why people look at their online lab results (i.e., health status, reassurance, health education, speed, self-management, and patient safety) and two themes about what people look for (i.e., abnormal and normal values, trends). Knowing what drives users and what information they are looking for can inform the design of online lab reporting, improve usefulness, and better satisfy user needs.
CovidGraph: Integrating COVID-19 Data
Authors: Henkel Ron , Guetebier Lea , Waltemath Dagmar
Published: May 2022

CovidGraph, developed by the HealthECCO community, is a platform designed to foster research and data exploration to fight COVID-19. It is built on a graph database and encompasses data sources from different biomedical data domains including publications, clinical trials, patents, case statistics, molecular data and systems biology models. The tool provides multiple interfaces for data exploration and thus serves as a single point of entry for data driven COVID-19 research. Availability and Implementation: CovidGraph is available from the project website: https://healthecco.org/covidgraph/. The source code and documentation are provided on GitHub: https://github.com/covidgraph.
Perception of the Communication Campaign for @choum a Symptom Reporting App: Insights from Semi Structured Interviews
Authors: Ehrler Frederic , Gaete Elias , De Ridder David , Loizeau Andrea , Guessous Idris
Published: May 2022

As an attempt to identify cluster of spread of COVID, we have developed the @choum functionality enabling individuals to signal when they perceived COVID-19 symptoms. The associated communication campaign did not encounter the expected success and only a limited amount of person did download the app. As an attempt to understand the barriers of use we have recruited a sample of general population to perform semi structured interview. Interview transcripts were analyzed using thematic analysis. Results highlight 3 profiles, engaged, critics and disengaged. We observe that these 3 profiles have different perception of the communication campaign, engaged participants being much more convinced by its message whereas disengaged people lack strongly of trust. This study helped us to identify what messages must be emphasized in order to attract critic people that may be convinced to use the tool.
CyberPharmacovigilance of Covid-19: Social Media Data Analytics
Authors: Ayumba Eustache Muteba
Published: May 2022

In this article, we present a methodology and a tool for extracting and analyzing information, reported by a social media monitor, of people who have taken drugs to treat Covid-19 and the adverse effects encountered.
Health Care Professionals’ Perspectives on the Uses of Patient-Generated Health Data
Authors: Guardado Sharon , Isomursu Minna , Giunti Guido
Published: May 2022

Integration of digital self-management solutions into health care processes requires the involvement of health care professionals in the adoption and use of the solutions as part of the care pathway. We conducted 23 interviews with diverse profiles of health care professionals participating in the treatment of chronic patients in three different countries. Our results indicate that health care professionals appeared relatively motivated at the prospect of having access to patient-generated data. Nevertheless, they appeared less confident in weighing what types of data could be collected efficiently through mobile devices and how it could be presented in ways that would provide value to the care process. Our results identify four broad categories for how patient-generated health data could be useful: monitoring, prevention, research, and transparency of condition parameters.
AI Diagnostic Technologies and the Gap in Colorectal Cancer Screening Participation
Authors: Ameen Saleem , Wong Ming Chao , Yee Kwang Chien , Nøhr Christian , Turner Paul
Published: May 2022

AI augmented clinical diagnostic tools are the latest research focus in colorectal cancer (CRC) detection. While the opportunity presented by AI-enhanced CRC diagnosis is sound, this paper highlights how its effectiveness with respect to reducing CRC-related mortality and enhancing patient outcomes may be limited by the fact that patient participation remains extremely low globally. This paper builds a foundation to consider how human factors tend to contribute to low participation rates and suggests that a more nuanced socio-technical approach to the development, implementation and evaluation of AI systems that is sensitive to the psycho-social and cultural dimension of CRC may lead to tools that increase screening uptake.
Semi-Structured Interviews to Evaluate a BCMA Implementation Trouble Areas
Authors: Descalzo Juan Marcos , Cassarino Melanie , Grande Ratti María Florencia , Smith María , Luna Daniel
Published: May 2022

Errors in medication administration involve risks to patient safety. “Bar-Coding Medication Administration” is implemented to prevent these errors. Adoption by nurses is one of the main determinants of their effectiveness. The Hospital Italiano de Buenos Aires implemented BCMA 6 years ago, but its adoption rate still finds resistance in certain sectors. We conducted semi-structured interviews with nursing staff to explore the barriers to the use in low-usage wards and explore the current perceptions of nurses. While nurses recognised the safety and usefulness of the BCMA system, they reported many difficulties. The feedback obtained through this process was useful for the implementation team to plan future interventions, priorities and improvements on the system. The semi-structured interview methodology proved useful as a continuous monitoring strategy.
viroCapt: A Bioinformatics Pipeline for Identifying Viral Insertion in Human Host Genome
Authors: Wack Maxime , Veyer David , Peneau Camille , Lameiras Sonia , Digan William , Nicolas Alain , Zucman-Rossi Jessica , Imbeaud Sandrine , Burgun Anita , Péré Hélène , Rance Bastien
Published: May 2022

Introduction: The implication of viruses in human cancers, as well as the emergence of next generation sequencing has permitted to investigate further their role and pathophysiology in the development of this disease. One such mechanism is the integration of portions of viral genomes in the human genome, as well as the specific action of viral oncogenes.inding integration sites and preserved oncogenes is still relying on heavy manual intervention. Methods: We developed an analysis and interpretation pipeline to determine viral insertions. Using data from directed viral capture, the pipeline conducts a crude genotyping phase to select reference viral genomes, identifies chimeric reads, extracts the putative human sequences to locate in the human reference genome, scores and ranks candidate junctions, and exports tabular and visual results. Results: We leverage common bioinformatics tools (bowtie2, samtools, blat), and a dedicated filtering and ranking algorithm, implemented in R, to infer candidate junctions and insertions. Static results (tables, figures) are produced, as well as an interactive interpretation tool developed as a shiny web app. Discussion: We validated this pipeline against published results of HPV, HBV, and AAV2 insertions and show good information retrieval.
Designing an Optimal Expansion Method to Improve the Recall of a Genomic Variant Curation-Support Service
Authors: Mottaz Anaïs , Pasche Emilie , Michel Pierre-André , Mottin Luc , Teodoro Douglas , Ruch Patrick
Published: May 2022

The importance of genomic data for health is rapidly growing but accessing and gathering information about variants from different sources is hindered by highly heterogeneous representations of variants, as outlined by clinical associations (AMP/ASCO/CAP) in their recommendations. To enable a smooth and effective retrieval of variant-containing documents from different resources, we developed a tool (https://goldorak.hesge.ch/synvar/) that generates for any given SNP – including variant not present in existing databases – its corresponding description at the genome, transcript and protein levels. It provides variant descriptions in the HGVS format as well as in many non-standard formats found in the literature along with database identifiers. We present the SynVar service and evaluate its impact on the recall of a genomic variant curation-support service. Using SynVar to search variants in the literature enables to increase the recall by +133.8% without a strong impact on precision (i.e. 93%).
Clustering Nursing Sentences – Comparing Three Sentence Embedding Methods
Authors: Moen Hans , Suhonen Henry , Salanterä Sanna , Salakoski Tapio , Peltonen Laura-Maria
Published: May 2022

In health sciences, high-quality text embeddings may augment qualitative data analysis of large amounts of text by enabling, e.g., searching and clustering of health information. This study aimed to evaluate three different sentence-level embedding methods in clustering sentences in nursing narratives from individual patients’ hospital care episodes. Two of these embeddings are generated from language models based on the BERT framework, and the third on the Sent2Vec method. These embedding methods were used to cluster sentences from 20 patient care episodes and the results were manually evaluated. Findings suggest that the best clusters were produced by the embeddings from a BERT model fine-tuned for the proxy task of predicting subject headings for nursing text.
Assessing the Quality of Direct-to-Consumer Teleconsultation Services in Canada
Authors: Noel Nikiema Jean , Stringer Eleah , Moreault Marie-Pierre , Pana Priscille , Laverdiere Marco , Régis Catherine , Denis Jean-Louis , Godard Béatrice , Breton Mylaine , Paré Guy , Shachak Aviv , Lai Claudia , Borycki Elizabeth M. , Kushniruk Andre W. , Motulsky Aude
Published: May 2022

The objective of this study was to describe and assess the quality of the direct-to-consumer medical teleconsultation landscape in three Canadian provinces. An environmental scan of primary care teleconsultation platforms was conducted in January 2022 to identify medical teleconsultation platforms in Quebec (Qc), Ontario, and British Columbia (BC). The quality of each teleconsultation platform was assessed using a modified version of the HONcode principles. Nineteen different direct-to-consumer medical teleconsultation platforms were identified across the three provinces. The quality of these teleconsultation platforms was very heterogeneous. The landscape of virtual primary care is changing rapidly in the Canadian ecosystem, and the transparency of current teleconsultation platforms could be improved.
SPEAKapp: Language as Digital Biomarker for Mental Health
Authors: Barattieri Di San Pietro Chiara , Simonetti Valentina , Bulgheroni Maria
Published: May 2022

Language has always been a rich source of amnestic information in the context of cognitive and affective disorders. Many of the language tests and metrics that are employed today have been designed when the only available technology was paper and pencil. Here we present a novel digital tool to administer and score a set of tests based on language.
EEG Spectral Changes Linked to Psychiatric Medications: Computational Pipeline for Data Mining and Analysis
Authors: Maxion Anna , Gaebler Arnim Johannes , Albiez Daniela , Mathiak Klaus , Zweerings Jana , Kutafina Ekaterina
Published: May 2022

The presented computational pipeline is designed to analyze drug-induced changes in EEG data from the Temple University EEG Corpus. The data is cleaned from artifacts, pre-processed, the averaged absolute and relative frequency powers are calculated and compared to a control group. Thus, different research hypotheses can be tested with the intention to reuse accessible data collections.