bluuebunny/crossref_metadata_2025 huggingface dataset:
Success Factors of an Early EHR System for Child and Adolescent Mental Health: Lessons Learned for Future Practice Data-Driven Decision Aids
Authors: Koochakpour Kaban , Nytrø Øystein , Westbye Odd Sverre , Leventhal Bennett , Koposov Roman , Bakken Victoria , Clausen Carolyn , Røst Thomas Brox , Skokauskas Norbert
Published: June 2022

This paper recounts the successful BUPdata, a discontinued electronic health record (EHR) system for Child and Adolescent Mental Health Services (CAMHS) in Norway. It was developed and owned by the national association for CAMHS and fulfilled needs for collaborative care, practice insight, and service management. It aimed to unify the requirements of government, administration, clinicians, patients, and researchers alike, with the goal of providing uniform quality of care nationally. When CAMHS became integrated with specialist healthcare, BUPdata was replaced with more a general EHR system offering far less functionality and insight into CAMHS practice. We have studied BUPdata, and interviewed stakeholders in order to develop decision aids based on practice data analysis and give clinicians and patients insight into successful local practice, collaboration patterns, and overview of local resources.
“Re-Materialized” Medical Data: Paper-Based Transmission of Structured Medical Data Using QR-Code, for Medical Imaging Reports
Authors: Lauriot Dit Prevost Arthur , Bentegeac Raphaël , Dequesnes Audrey , Billiau Adrien , Baudelet Emmanuel , Legleye Rémi , Hubaut Marc-Antoine , Cassagnou Michel , Puech Philippe , Besson Rémi , Chazard Emmanuel
Published: June 2022

Although paper-based transmission of medical information might seem outdated, it has proven efficient, and remains structurally safe from massive data leaks. As part of the ICIPEMIR project for improving medical imaging report, we explored the idea of structured data storage within a medical report, by embedding the data themselves in a QR-Code (and no URL-to-the-data). Three different datasets from ICIPEMIR were serialized, then encoded in a QR-Code. We compared 4 compression algorithms to reduce file size before QR-Encoding. YAML was the most concise format (character sparing), and allowed for embedding of a 2633-character serialized file within a QR-Code. The best compression rate was obtained with gzip, with a compression ratio of 2.32 in 15.7ms. Data were easily extracted and decompressed from a digital QR-Code using a simple command line. YAML file was also successfully recovered from the printed QR-Code with both Android and iOS smartphone. Minimal detected size was 3*3cm.
An Improved Immunization Record to Support Vaccination During the COVID-19 Pandemic at a University Hospital in Argentina
Authors: Descalzo Juan M. , Verdineli Julian , Nuñez Joia , Díaz Soledad V. , Gambarte Maria L. , Minoletti Sebastián , Blanco Matías H. , Jauregui Oscar I. , Rizzato Lede Daniel A. , Otero Carlos M. , Luna Daniel R.
Published: June 2022

WHO and UNICEF highlight vaccination as the most cost-effective method of prevention of infectious diseases. An effective public health strategy requires efficient tracking of vaccination to assess coverage, safety, and efficacy of these vaccines. Paper-based immunization records are still being used in most low and middle-income countries. Adequate Electronic Logistic Management Information Systems, Immunization Registries and Records are crucial for proper data collection and analysis, and for making better decisions at an individual and at a population level. In this paper we share our experience in the redesign of an interoperable immunization record to track vaccination, including the recently developed vaccines for the novel coronavirus SARS-CoV-2 (COVID-19).
Analysis of Causal Relationships in Integrated Ontologies of Diseases, Phenotypes, and Radiological Diagnosis
Authors: Kahn Jr. Charles E.
Published: June 2022

Biomedical ontologies encode knowledge in a form that makes it computable. The current study used the integration of three large biomedical ontologies—the Disease Ontology (DO), Human Phenotype Ontology (HPO), and Radiology Gamuts Ontology (RGO)—to explore inferred causal relationships between high-level DO and HPO concepts. The principal DO categories were defined as the 7 direct subclasses of the top-level Disease class, excluding Disease of anatomical entity, plus the 12 direct subclasses of the latter term. The principal HPO categories were defined as the 25 direct subclasses of HPO’s Phenotypic abnormality class. All causal relationships were tallied between members of the DO and HPO principal categories through their causal relationships in RGO. The analysis provides an understanding of the hierarchical organization of RGO terms, and offers insights into new relationships between DO and HPO classes.
Evaluation of Criteria2Query: Towards Augmented Intelligence for Cohort Identification
Authors: Liu Cong , Liu Hao , Ta Casey , Roger James , Butler Alex , Lee Junghwan , Kim Jaehyun , Shang Ning , Weng Chunhua
Published: June 2022

Electronic healthcare records data promises to improve the efficiency of patient eligibility screening, which is an important factor in the success of clinical trials and observational studies. To bridge the sociotechnical gap in cohort identification by end-users, who are clinicians or researchers unfamiliar with underlying EHR databases, we previously developed a natural language query interface named Criteria2Query (C2Q) that automatically transforms free-text eligibility criteria to executable database queries. In this study, we present a comprehensive evaluation of C2Q to generate more actionable insights to inform the design and evaluation of future natural language user interfaces for clinical databases, towards the realization of Augmented Intelligence (AI) for clinical cohort definition via e-screening.
Interactive Similarity-Based Search of Clinical Trials
Authors: Sun Yingcheng , Tang Jiaqi , Butler Alex , Liu Cong , Fang Yilu , Weng Chunhua
Published: June 2022

The rapid growth of clinical trials launched in recent years poses significant challenges for accurate and efficient trial search. Keyword-based clinical trial search engines require users to construct effective queries, which can be a difficult task given complex information needs. In this study, we present an interactive clinical trial search interface that retrieves trials similar to a target clinical trial. It enables user configuration of 13 clinical trial features and 4 metrics (Jaccard similarity, semantic-based similarity, temporal overlap and geographical distance) to measure pairwise trial similarities. Among 1,007 coronavirus disease 2019 (COVID-19) trials conducted in the United States, 91.9% were found to have similar trials with the similarity threshold being 0.85 and 43.8% were highly similar with the threshold 0.95. A simulation study using 3 groups of similar trials curated by COVID-19 clinical trial reviews demonstrates the precision and recall of the search interface.
Quality Assessment of Meta-Analyses on Cervical Cancer
Authors: Milosavljevic Sofia , Yang Pei-Yin , Kang Hong , Mullen Patricia Dolan , Gong Yang
Published: June 2022

Meta-analysis (MA) quantitatively summarizes the findings of independent studies and is considered the highest quality of evidence for evidence-based medicine. However, issues in reporting and methodological rigor of MA hamper reproducibility and create the potential for bias. By applying PRISMA reporting guideline and AMSTAR2 execution guidelines on 40 cervical cancer MA samples covering topics such as interventions and risk factors, we determined the extent to which MA execution adhered to best practice guidelines. The results show that the elements with least adherence include “review methods established before MA” and “principal summary measures defined” (each 32.5% per PRISMA) and “characteristics of included studies” (31.3% per AMSTAR2) which undermine reproducibility and increase the risk of bias. This initial work presents common pitfalls in MA and is intended to improve awareness of these issues for clinicians who are interested in conducting MA and to pave the way toward quality improvement via informatics approaches.
Should App Self-Management Mean Self-Control? A Quantiative Study on App Supported Diabetes Self-Management
Authors: Reineke Lukas , Hübner Ursula , Kröner Saskia , Liebe Jan-David
Published: June 2022

Apps have been attested to empower patients regarding disease self-management through numerous studies. However, it is still unclear what factors determine the perception of patients whether an app is a useful tool for this purpose. A multiple regression model that was informed by the Technology Acceptance Model (TAM 2) was tested based on the answers of 235 app users with Diabetes type 1 or 2. The model accounted for 59.2% of the variance of the perceived degree of self-management. Factors belonging to the relevance-usefulness-quality complex as well as factors reflecting the patient’s self-control were found to be significant in the model. Patient demographics, i.e. age, gender, app experience and type of Diabetes did not play any significant role. In conclusion, this study raises the question whether apps should be designed to strengthen self-management in the sense of self-control (e.g. own measurements, diary) as opposed to guiding and advice giving.
Telerehabilitation for Patients with Cancer: A Scoping Review
Authors: Rocco Patricia , Finkelstein Joseph
Published: June 2022

This study was aimed at identifying how telemedicine is used for rehabilitation of patients with cancer. An electronic literature search was conducted using the PubMed database covering January 2015 to October 2020. To be included in the review, studies had to report telerehabilitation interventions for patients with cancer. Randomized controlled trials, quasi-experimental studies, as well as feasibility and usability studies were included, and reviews were excluded. Overall, 33 eligible studies were found but only 22 were considered for inclusion. After a detailed analysis, 16 studies were included. Most of the studies concluded that telehealth systems supporting physical exercise were effective to improve function, quality of life, pain, satisfaction and muscle strength. Limitations in most of the studies included non-randomized design and limited number of subjects. We conluded that more studies are needed for stronger evidence of this type of treatment and to facilitate clinical practice in this field.
Review of the Performance Metrics for Natural Language Systems for Clinical Trials Matching
Authors: Kim Jeongeun , Quintana Yuri
Published: June 2022

Natural Language Processing (NLP) has been adopted widely in clinical trial matching for its ability to process unstructured text that is often found in electronic health records. Despite the rise in the new tools that use NLP to match patients to eligible clinical trials, the comparison of these tools is difficult due to the lack of consistency in how these tools are evaluated. The ground truth or reference that the tools use to assess results varies, making it difficult to compare the robustness of the tools against each other. This paper alarms the lack of definition and consistency of ground truth data used to evaluate such tools and suggests two ways to define a gold standard for the ground truth in small and large-scale studies.
Noninvasive Glioma Grading with Deep Learning: A Pilot Study
Authors: Danilov Gleb , Korolev Vladislav , Shifrin Michael , Ilyushin Eugene , Maloyan Narek , Saada Daniel , Ishankulov Timur , Afandiev Ramin , Shevchenko Alexander , Konakova Tatyana , Tsukanova Tatyana , Shugay Svetlana , Pronin Igor , Potapov Alexander
Published: June 2022

Gliomas are the most common neuroepithelial brain tumors, different by various biological tissue types and prognosis. They could be graded with four levels according to the 2007 WHO classification. The emergence of non-invasive histological and molecular diagnostics for nervous system neoplasms can revolutionize the efficacy and safety of medical care and radically reduce healthcare costs. Our pilot study aimed to evaluate the diagnostic accuracy of deep learning (DL) in subtyping gliomas by WHO grades (I–IV) based on preoperative magnetic resonance imaging (MRI) from Burdenko Neurosurgery Center’s database. A total of 707 MRI studies was included. A “3D classification” approach predicting tumor type for the entire patient’s MRI data showed the best result (accuracy = 83%, ROC AUC = 0.95), consistent with that of other authors who used different methodologies. Our preliminary results proved the separability of MR T1 axial images with contrast enhancement by WHO grade using DL.
Adoption of Digital Pain Manikins for Research Data Collection: A Systematic Review
Authors: Ali Syed Mustafa , Lee Rebecca R. , Chiarotto Alessandro , Dixon William G. , McBeth John , van der Veer Sabine N.
Published: June 2022

Chronic pain is common and disabling. Researchers need robust methods to collect pain data in large populations to enhance knowledge on pain prevalence, causes and treatment. Digital pain manikins address this by enabling self-reporting of location-specific pain. However, it is unknown to what extent pain studies adopted digital manikins for data collection. Therefore, we systematically searched the literature. We included 17 studies. Most were published after 2017, collected pain data cross-sectionally in ≥50 participants, and reported pain distribution and pain extent as manikin-derived summary metrics. Across the studies, 13 unique manikins were used, of which four had been evaluated. Our review shows that adoption of digital pain manikins in research settings has been slow. Harnessing the digital nature of manikins, enabling use of personal devices, and assessing and improving the reliability, validity and responsiveness of digital manikins will expedite their adoption as digital data collection tools for pain research.
Prediction of Incident Dementia Using Patient Temporal Health Status
Authors: Fu Sunyang , Ibrahim Omar A. , Wang Yanshan , Vassilaki Maria , Petersen Ronald C. , Mielke Michelle M. , St Sauver Jennifer , Sohn Sunghwan
Published: June 2022

Dementia is one of the most prevalent health problems in the aging population. Despite the significant number of people affected, dementia diagnoses are often significantly delayed, missing opportunities to maximize life quality. Early identification of older adults at high risk for dementia may help to maximize current quality of life and to improve planning for future health needs in dementia patients. However, most existing risk prediction models predominantly use static variables, not considering temporal patterns of health status. This study used an attention-based time-aware model to predict incident dementia that incorporated longitudinal temporal health conditions. The predictive performance of the time-aware model was compared with three traditional models using static variables and demonstrated higher predictive power.
Applying Formal Concept Analysis for the Recognition of Infant Mortality Patterns
Authors: Marzano Lorenzo , Nobre Cristiane , Zárate Luis , Song Mark
Published: June 2022

Infant mortality (IM), an index that corresponds to the number of deaths among children up to one year, is an important social indicator of a region. It generally reflects the conditions of socioeconomic development – in addition, the access and quality of resources available for maternal and child health care. Monitoring its magnitude, thus, can help in the definition of public policies for its confrontation. The main causes of IM can be also associated with biological, behavioral, and public health issues. In this work, implication and association rules based on Formal Concept Analysis are used to recognize patterns in births occurring in the state of Amapá (located in the Brazilian Amazon), where the index of infant mortality is more severe.
Interpreting the Human Longevity Profile Through Triadic Rules – A Case Study Based on the ELSA-UK Longitudinal Study
Authors: Noronha Marta D.M. , Nobre Cristiane N. , Song Mark A.J. , Zárate Luis E.
Published: June 2022

Human aging is a complex process with several factors interacting. One of the ways to identify patterns about human aging is longitudinal population studies. In this work, we identified longevity profiles through a process of knowledge discovery. After identifying the profiles, we apply triadic rules which allow extracting rules of implication with conditions. These rules can be used to identify related factors, in the various waves, of longitudinal studies, which can better explain the conditions that favor longevity profiles.The results show that the triadic analysis is efficient to allow the analysis of the temporal evolution of clinical or environmental conditions that favor certain profiles when databases of longitudinal studies are considered.
Using Machine Learning on Imbalanced Guideline Compliance Data to Optimize Multidisciplinary Tumour Board Decision Making for the Management of Breast Cancer Patients
Authors: Le Thien My-Anh , Redjdal Akram , Bouaud Jacques , Séroussi Brigitte
Published: June 2022

Complex breast cancer cases that need further multidisciplinary tumor board (MTB) discussions should have priority in the organization of MTBs. In order to optimize MTB workflow, we attempted to predict complex cases defined as non-compliant cases despite the use of the decision support system OncoDoc, through the implementation of machine learning procedures and algorithms (Decision Trees, Random Forests, and XGBoost). F1-score after cross-validation, sampling implementation, with or without feature selection, did not exceed 40%.
A User-Centered Evaluation of a COVID-19 Intelligent Query System (COVID-IQS)
Authors: Wu Danny T.Y. , Zhou Fangyu , Su Wu-Chen , Vu Hoang , Sahu Piyush , Harnett Brett , Chiu Tseng-Ping , Vogel Craig , Lee James J.
Published: June 2022

As the fight against COVID-19 continues, it is critical to discover and accumulate knowledge in scientific literature to combat the pandemic. In this work, we shared the experience in developing an intelligent query system on COVID-19 literature. We conducted a user-centered evaluation with 12 researchers in our institution and identified usability issues in four categories: distinct user needs, functionality errors, suboptimal information display, and implementation errors. Furthermore, we shared two lessons for building such a COVID-19 literature search engine. We will deploy the system and continue refining it through multiple phases of evaluation to aid in redesigning the system to accommodate different user roles as well as enhancing repository features to support collaborative information seeking. The successful implementation of the COVID-IQS can support knowledge discovery and hypothesis generation in our institution and can be shared with other institutions to make a broader impact.
Towards Reducing Health Information Inequities in the Caribbean: The Eastern Caribbean Health Outcomes Research Network Data Sharing Platform Usability Study
Authors: McCall Terika , Date Stephanie , Alexis Dorothy , Whiteman Stephanie , Dick Salihah , Marenco Luis , Campbell Britton Meredith , Tessier-Sherman Baylah , Brandt Cynthia , Wang Karen
Published: June 2022

There is a dearth of health research among Caribbean populations. Underrepresented individuals are affected by structural and data inequities that limit the usefulness, availability, and accessibility to health information systems and research-generated data. To overcome this limitation, a data sharing platform was created for the Eastern Caribbean Health Outcomes Research Network Cohort Study. This study aimed to evaluate the usability of the platform. Usability testing was conducted remotely, via video conferencing, using a cognitive walkthrough and think-aloud protocol. Participants completed a self-administered web-based survey which included an adapted version of the System Usability Scale (SUS). The results showed (N=16) overall average SUS score was 73.1 (SD±21.0), translating to a ‘good’ usability rating. Most recommendations for improvement focused on navigation and error prevention. Participatory data sharing platforms have the potential to reduce health information inequities in the Caribbean, however, usability testing should be conducted to improve user satisfaction and increase engagement.
Artificial Intelligence and Clinical Decision Support Systems or Automated Interpreters: What Characteristics Are Expected by French General Practitioners?
Authors: Tabla Smaïn , Calafiore Matthieu , Legrand Bertrand , Descamps Axel , Andre Charlotte , Rochoy Michaël , Chazard Emmanuel
Published: June 2022

Development of artificial intelligence (AI) modules should rely on technical progress, but also on users’ needs. Our objective is to identify criteria that make a hypothetical AI module desirable for general practitioners (GPs). Method: random selection of 200 French GPs, and paper-based questionnaire. Results: the population was representative. GPs expect AI modules to diagnose or eliminate an urgent pathology for which they are not competent and for which specialists are not available. They also demand interoperability, automated electronic health record integration and facilitated information sharing. GPs would like AI modules to make them save time, simplify some procedures and delegate tasks to the secretary. They expect AI modules to allow them to associate the patient with the care, to reassure him or her, and to personalize the care. Interestingly, GPs would also rely on a machine to cut off abusive requests, such as work stoppages or certificates of convenience.
Your Quest Begins Now! EBMQuest, a Digital Interactive Fiction Module for Medical Student Engagement in Evidence-Based Practice
Authors: Varan Aiden K. , Winkel Kenneth , McKenzie Rosemary
Published: June 2022

Although evidence-based medicine (EBM) has gained increasing focus in medical education, there remains considerable need for innovative approaches to engage learners. We developed a novel online interactive fiction module “EBMQuest”, where students navigate three clinical scenarios requiring use of EBM resources for successful progression. Student feedback was strongly positive, with an overall program rating of 4.64 (Good-Very Good). Online interactive fiction should be further explored as a means of delivering innovative medical education.
Customizable Serious Speech Therapy Games with Dynamic Difficulty Adjustment for Children with Sigmatism
Authors: Martins Sofia , Cavaco Sofia
Published: June 2022

Children with speech sound disorders should attend speech and language therapy and should practice the speech exercises regularly to surpass their speech difficulties. Since doing the speech exercises often may be tedious, there is the need to motivate children to practice them. During the COVID-19 pandemic, speech and language pathologists had the need to adapt their procedures to others with less physical contact. Here, we propose two serious games to motivate children with sigmatism on doing the speech exercises, which can be used at home and during face-to-face and online speech therapy sessions. The games use automatic speech recognition to classify speech productions. Visual and auditory feedback are used to help children understand their performance, and a hint system is used to help them perform the exercises correctly. A dynamic difficulty adjustment system is used to change the level of difficulty according to the child’s speech performance in previous trials.
Using EHR Data to Identify Social Determinants of Health Affecting Disparities in Cancer Survival
Authors: Cui Wanting , Finkelstein Joseph
Published: June 2022

The aim of this pilot study was to identify social determinants of health (SDH) that affect disparities in cancer survival. A limited dataset was generated by querying electronic medical records (EHR) from an academic medical center in New York City between January 2003 and November 2020. Socio-demographic characteristics that affected survival in 22,096 cancer patients were analyzed using descriptive statistics and logistic regression analyses. Two subsets of adult patients were identified: patients who were deceased less than 1 year after diagnosis and patients who survived over 5 years after diagnosis. Percentage of individuals with short survival in Blacks and Whites was respectively 41.4% and 22.2% for lung cancer, 9.8% and 7.1% for colorectal cancer, 2.9% and 0.7% for breast cancer, 6.8% and 4.0% for multiple myeloma, and 1.4% and 0.8% for prostate cancer. Logistic regression identified SDH factors increasing likelihood of shorter survival that included older age, and being male, Black or Hispanic. We concluded that further analysis of a broader spectrum of SDH factors is warranted.
Use of Digital Health Technology for Seeking Health Information Among Older Family Caregivers
Authors: Baik Dawon , Willems Emileigh
Published: June 2022

There is little research on the relationship between digital health technology use and health services, self-efficacy, health status, and health information seeking behavior among older family caregivers. We conducted a secondary analysis of the US Health Information National Data and found that older family caregivers with a regular healthcare provider are more likely to use digital health technology, which increases their confidence in obtaining health information (β=0.075, z=2.015, p<0.044).
Current Status of Contrast Computed Tomography Examination for Diagnosing Acute Pulmonary Thromboembolism
Authors: Shida Keiichi , Okumura Syuuichirou , Okikawa Takashi , Yamamuro Megumi
Published: June 2022

The purpose of this study was to identify instances of unnecessary contrast-enhanced computed tomography (CT) scans performed at the time of diagnosis in patients with pulmonary thromboembolism at the emergency department of Saiseikai Kumamoto Hospital in Kumamoto Prefecture, Japan, between April 1, 2015, and March 31, 2020. The decision criteria for unnecessary contrast-enhanced CT scans included a Wells score of low or moderate risk, a D-dimer level <1.0 μg/mL, and no shock symptoms, or a negative finding for pulmonary thromboembolism. Consequently, 27 patients were considered to have undergone unnecessary contrast-enhanced CT scans. This equated to approximately 15.6% of the study population.
TECIPOT: Study for the Evaluation of New Technologies and Process Engineering Applied to the Optimization of Hospital Transfers
Authors: Miguez Carlos , Moreno Alberto , Moreno Jesús , Gonzalez Victor , Salas Samuel , Herrerias Juan
Published: June 2022

There is a need for coordinating and manage the information flow between clinical, nursing, ancillary, cleaning and administrative staff to optimize patient transfers during admission and discharge. TECIPOT project proposes the incorporation of new technologies associated with the optimization of emergency circuits to improve the efficiency in the management of patients in the center, as well as improve the perception of patients and professionals about the processes of transfers of emergency patients, observation and discharge from the Hospital. The project proposes a 24 month study to evaluate the impact on healthcare processes.
Can We Do Better than Gesturing? Requirements for a Digital Communication Aid to Support Non-Verbal Communication in Paediatric Emergency Care
Authors: Kaufmann Beatrice , Haldemann Anouk , Lueg Christopher , Olalia Loraine , Thilo Friederike , Denecke Kerstin
Published: June 2022

Providing urgent and emergency care to migrant children is often hampered or delayed. Reasons for this are language barriers when children, and their care givers, don’t speak any of the languages commonly spoken in Switzerland, which include German, French, Italian, and English. By a participatory design process, we want to develop a novel image-based digital communication aid tailored to the needs of migrant patients and nurses within Swiss paediatric clinics.
Using Facebook™ as a Platform for Remote Patient Care to Address Rehabilitation Needs in a Resource-Limited Environment During a Crisis
Authors: Karunaratne M.D.A.I. , Rajakulathunga D.C. , Jayalath J.S.S. , Silva S.N.
Published: June 2022

The Covid 19 Pandemic affected Physiotherapy Clinics as much as it did all Clinical Services Provisions all over the world. This paper discusses a model where Facebook social media platform was successfully used as an emergency platform to deliver clinical services to the clients of a Physiotherapy Clinic in a Developing Country, during the Covid 19 pandemic.
COVID-19 Geographical Maps and Clinical Data Warehouse PREDIMED
Authors: Artemova Svetlana , Caporossi Alban , Cancé Christophe , Madiot Pierre-Ephrem , Nemoz Benjamin , Larrat Sylvie , Moreau-Gaudry Alexandre , Bosson Jean-Luc
Published: June 2022

PREDIMED, Clinical Data Warehouse of Grenoble Alps University Hospital, is currently participating in daily COVID-19 epidemic follow-up via spatial and chronological analysis of geographical maps. This monitoring is aimed for cluster detection and vulnerable population discovery. Our real-time geographical representations allow us to track the epidemic both inside and outside the hospital.
Bottom-Up Natural Language Processing Based Evaluation of the Fitness of UMLS as a Semantic Source for a Computer Interpretable Guidelines Ontology
Authors: Despotou George , Korkontzelos Ioannis , Arvanitis Theodoros N.
Published: June 2022

Background: CIGs languages consist of approach specific concepts. More widely used concepts, such as those in UMLS are not typically used. Objective: An evaluation of UMLS concept sufficiency for CIG definition. Method: A popular guideline is mapped to UMLS concepts with NLP. Results are reviewed to evaluate gaps, and appropriateness. Results: A significant number of the guideline text mapped to UMLS concepts. Conclusions: The approach has shown promise and highlighted further challenges.
ODIASP: Clinically Contextualized Image Analysis Using the PREDIMED Clinical Data Warehouse, Towards a Better Diagnosis of Sarcopenia
Authors: Charrière Katia , Madiot Pierre-Ephrem , Artemova Svetlana , Tep Pungponhavoan , Lenne Christian , Cohard Brigitte , Caporossi Alban , Boudry Isabelle , Meyzenc Juliette , Ferretti Gilbert , Bricault Ivan , Giai Joris , Bosson Jean-Luc , Fontaine Eric , Bétry Cécile , Moreau-Gaudry Alexandre
Published: June 2022

Big Data and Deep Learning approaches offer new opportunities for medical data analysis. With these technologies, PREDIMED, the clinical data warehouse of Grenoble Alps University Hospital, sets up first clinical studies on retrospective data. In particular, ODIASP study, aims to develop and evaluate deep learning-based tools for automatic sarcopenia diagnosis, while using data collected via PREDIMED, in particular, medical images. Here we describe a methodology of data preparation for a clinical study via PREDIMED.
Privacy-Preserving Partner Notification Service to Control Sexually Transmitted Infections
Authors: Kakalou Christine , Polychronidou Eleftheria , Drosou Vicky , Dimitriadis Vlasios K. , Dermaris Thomas , Kordonias Rafael , Papaprodromou Aris , Tsirelis Triantafillos , Maramis Christos , Votis Konstantinos , Tzovaras Dimitrios , Savarino Domenico , Maffeo Manuel , Jasic Nedim , Nemeth Blažić Tatjana , Dominković Zoran , Pogledić Dubravko , Jovovic Iva , Simkunaite-Zazecke Agne , Stoniene Loreta , Sammut Antonella , Cosmaro Lella , Natsiavas Pantelis
Published: June 2022

Partner Notification (PN) processes are typically part of wider combination prevention efforts and focus on the notification of sexual partners to prevent Sexually Transmitted Infections (STIs), including Human Immunodeficiency Viruses and viral hepatitis. We present a free, voluntary, anonymous and GDPR-compliant Partner Notification service that offers enhanced security and privacy through a web and mobile application via a unique random codes.
Experiences in Using KoBo Collect and KoBo Toolbox in a Cross-Sectional Dog Population and Rabies Knowledge and Practices Household Survey in the Philippines
Authors: Dizon Timothy John R. , Saito Nobuo , Reñosa Mark Donald C. , Bravo Thea Andrea P. , Silvestre Catherine J. , Endoma Vivienne F. , Guevarra Jerric Rhazel B. , Quiambao Beatriz P. , Nishizono Akira
Published: June 2022

We used KoBo Collect and KoBo Toolbox as an electronic data capture platform for a dog population and rabies knowledge and practices community survey in the Philippines. It has allowed for easy design and deployment of an electronic form with minimal technical knowledge from the investigators. Using this platform allowed for shorter training for data collectors, minimal errors during data collection, and faster turn-around time for data cleaning and analysis.
GeoHealth: Geographic Information System for Health Management and Clinical, Epidemiological and Translational Research
Authors: Moreno Alberto , Moreno Jesus , González Victor , Salas Samuel , Segura Carmen , de Luque Virginia , Cuadri Pastora , Guardia Pedro , Luque Luis , Vilches Ángel
Published: June 2022

This project aims to develop a system for clinical, epidemiological and translational research capable of associating contextual variables and geospatial data with clinical patient information. The GeoHealth system will include a section to perform exploratory analysis that will help identify risk factors to optimize clinical decision making.
My Contraceptive Choice: A Decision Support Tool for College Women
Authors: Redman Molly , Brian Jenny , Wang Dongwen
Published: June 2022

We developed an online decision aid, My Contraceptive Choice (MCC), for college women to select the appropriate birth control methods. MCC consists of a short quiz, customized recommendations, and educational resources. Evaluations from a focus group, an online survey, and test cases showed that the tool is accurate, usable, and useful. Future work is required to further improve MCC’s compliance with user needs/preferences and to include additional resources to make it more useful.
RETRACTED: Developing Android, iOS Apps for Mobile-Enhanced Prevention Support (MEPS) for Men Who Have Sex with Men (MSM) and Transgender Women (TW) Leaving Jail in South Los Angeles in the USA
Authors: Mukherjee Sukrit , Edwards Gabriel G. , Harawa Nina
Published: June 2022

This article has been withdrawn from publication at the request of the second and third author, Dr. Edwards and Dr. Harawa.
Stakeholder Mapping on the Development of Digital Health Interventions for Self-Management Among Patients with Chronic Obstructive Pulmonary Disease in China
Authors: An Qingfan , Kelley Marjorie M. , Yen Po-Yin
Published: June 2022

Chronic Obstructive Pulmonary Disease (COPD) is a progressive lung disease consisting of chronic bronchitis and emphysema. Digital Health Interventions (DHIs) can improve COPD patients’ self-management. However, the market penetration of DHIs is lower than expected. Using stakeholder mapping, healthcare providers identified opportunities for design and development of sustainable DHIs. Two different stakeholder maps were identified. These maps demonstrated the importance of utilizing structured mapping techniques to understand roles of different stakeholders, and addressing regulatory and practice needs to ultimately support patient self-management.
Telerehabilitation Based on Markerless Motion Capture and IMT-2020 (5G) Networks
Authors: Oyama Shintaro , Saeki Masaomi , Kaneta Satoshi , Shimoda Shingo , Yoneda Hidemasa , Hirata Hitoshi
Published: June 2022

Eldercare programs such as health consultations and physiotherapy that improve the well-being and extend the life expectancy of people in rural or sparsely populated areas is a socially important though costly problem. We ran a pilot project to test the effectiveness potential of telerehabilitation using markerless motion capture technology integrated in a fast and low-latency IMT-2020 (5G) mobile network. Accelerating technological innovations and the surge in advances of telehealth will greatly impact conventional home visit or outpatient rehabilitation services, working in concert with or even supplanting them, given the potential lower cost and better utilization of time.
Design Recommendations for Presenting Clinical Guidelines on Mobile Devices
Authors: Mitchell James , de Quincey Ed , Pantin Charles , Mustfa Naveed
Published: June 2022

Some areas of clinical practice are still required to access and utilise clinical information that is inefficient or restrictive. Therefore, mobile device information delivery is becoming a key factor. However, recommendations on presenting clinical information on mobile devices are limited or not optimised for modern mobile design. Results from user-centred design studies inform the creation of a set of recommendations to assist in creating and delivering clinical guidelines on mobile devices.
Co-Design Approaches Involving Older Adults in the Development of Electronic Healthcare Tools: A Systematic Review
Authors: Cole Amy , Adapa Karthik , Richardson Daniel R. , Mazur Lukasz M.
Published: June 2022

We present evidence on the current state of utilizing co-design approaches involving older adults in developing electronic healthcare tools (EHTs). Research gaps were identified in defining the stages, involvement processes, and levels of participation using existing theoretical frameworks. Future studies should explore both involvement processes and levels of participation to optimally empower and collaborate with older adults in developing EHTs.
Building Cancer Control Capacity in Health Professionals Through Telementoring: A Survey Study of a Cancer Prevention and Survivorship Care ECHO Program
Authors: Milgrom Zheng Z. , Severance Tyler S. , Scanlon Caitlin M. , Carson Anyé T. , Janota Andrea D. , Vik Terry A. , Duwve Joan M. , Dixon Brian E. , Mendonca Eneida A.
Published: June 2022

Project Extension for Community Healthcare Outcomes (Project ECHO©) was developed to democratize knowledge among health professionals in underserved communities. Evidence supporting the use of this model for cancer control is limited. Using surveys adapted from Moore’s evaluation framework, we evaluated the training outcomes of an ECHO program on cancer prevention and survivorship care. The study provides preliminary evidence that the ECHO model is a feasible way to build cancer control capacity among the healthcare workforce.
Artificial Intelligence-Based Mobile Application for Emotion Sensing for Children Through Art
Authors: Ali Nashva , Abdrazaq Alaa , Shah Zubair , Househ Mowafa
Published: June 2022

In this paper, we develop an artificial intelligence (A.I.) based Emotion Sensing Recognition App (ESRA) to help parents and teachers understand the emotions of children by analyzing their drawings. Four different experiments were conducted using a combination of two datasets. The deep learning model was trained using the Fastai library in Python. The model classifies the drawings into positive or negative emotions. The model accuracy ranged from 55% to 79% in the four experiments.
A fast encryption method for enterprise financial data based on blockchain
Authors: Kong Lingmei
Published: June 2022

Aiming at the problems of poor encryption security and long encryption time in the existing enterprise financial data encryption, a fast encryption method of enterprise financial data based on blockchain is proposed. Firstly, the enterprise financial data is collected from the enterprise source database with the help of ETL Technology, and the collection is completed with the help of full extraction; Then, the interference data in the data is filtered with the help of Bloom filter, and the data index position is determined with the help of hash function mapping to complete the preprocessing. Finally, with the help of the data layer, network layer, consensus layer, motivation layer and application layer in the blockchain, the data and related encrypted data and timestamp are encrypted in each node, and the data encryption key is generated to complete the rapid encryption of enterprise financial data. The experimental results show that the security coefficient of enterprise financial data encrypted by the proposed method is high, and the encryption time is short.
Development of two-dimensional beam hardening correction for X-ray micro-CT
Authors: Davis Graham R.
Published: June 2022

BACKGROUND: Beam-hardening in tomography with polychromatic X-ray sources results from the nonlinear relationship between the amount of substance in the X-ray beam and attenuation. Simple linearisation curves can be derived with the use of an appropriate step wedge, however, this does not yield good results when different materials are present whose relationships between X-ray attenuation and energy are very different. OBJECTIVE: To develop a more accurate method of beam-hardening correction for two-phase samples, particularly immersed or embedded biological hard tissue. METHODS: Use of a two-dimensional step wedge is proposed in this study. This is not created physically but is derived from published X-ray attenuation coefficients in conjunction with a modelled X-ray spectrum, optimised from X-ray attenuation measurements of a calibration carousel. To test this method, a hydroxyapatite disk was scanned twice; first dry, and then immersed in 70% ethanol solution (commonly used to preserve biological specimens). RESULTS: With simple linearisation the immersed disk reconstruction exhibited considerable residual beam hardening, with edges appearing approximately 10% more attenuating. With 2-dimensional correction, the attenuation coefficient showed only around 0.5% deviation from the dry case. CONCLUSION: Two-dimensional beam-hardening correction yielded accurate results and does not require segmentation of the two phases individually.
FORMATION SPECIFICITY AND QUALITY ASSESSMENT CRITERIA OF FUNCTIONAL CONNECTIONS IN FLEXIBLE LEARNING SPACES OF EXTRACURRICULAR EDUCATION INSTITUTIONS
Authors: Vasylchenko Daria
Published: June 2022

The article is devoted to the study of educational spaces organization in extracurricular education institutions. A list of criteria for assessing the quality of functional connections between classroom zones has been determined. The work is based on the typological distribution of the study areas of into zones of individual (personalized) work, group (team) work, mass work (collective work, social meetings, intergroup work), on the conditional functional zones’ division according to the work scenario into independent studying zones and teacher-accompanied learning areas. The purpose of this work is to identify criteria for functional connections quality assessing and to determine the areas usage efficiency coefficient when using various scenarios of educational work in the learning spaces.

Functional connections formation specificity in flexible learning spaces lies in the need for a variable combination of work and training zones according to different scenarios, as well as specific requirements - the formation of zones with a high level of sound insulation, compliance with sanitary and hygienic requirements for educational environments - which are determined by the design task. The assessment of functional connections quality is determined on the basis of qualitative and quantitative indicators. Qualitative indicators include the presence of landmarks in the environment, color solution, selection of materials, ergonomic criterion, sanitary and hygienic criterion, the degree of learning environment accessibility. The quantitative indicators include the ratio of useful area indicators to the total area. The closer this indicator is to 1, the more efficiently the area of the institution is used.

The work defines the approximate percentage ratios between transit, purely educational and general areas of educational areas, which are used in modern design solutions and can serve as a reference ratio of educational spaces for new design solutions. In the work, based on the analysis of design solutions, a coefficient was determined, which will allow to determine more accurately the total and useful area of the extracurricular education institution, designed for certain types of work.
MANOR OF THE SOCIETY FOR EMERGENCY MEDICINE IN KYIV. HISTORY, ARCHITECTURE AND SIGNIFICANCE FOR THE CITY
Authors: Lienkova Maryna , Bulakh Irina
Published: June 2022

Today, the issue of restoring and preserving culture is more relevant than ever for Ukraine. After all, awareness of its significance is the basis of self-awareness of the individual in the context of cultural diversity. Our country has a large number of architectural heritage sites from different periods, which illustrates our multinational culture. However, the problem of uncontrolled construction in the historical center, motivated solely by investment benefits, directly harms the monuments of architecture and urban planning. And the silence of this issue is fraught with their complete extermination and the loss of identity by the city. The objective of the article is also to highlight the value of architectural heritage objects for Ukraine. The article considers an outstanding monument of architecture and urban planning of Kyiv, the Estate of the Ambulance Society. Its history from the moment of construction to the problems of the present, the architecture of facades, elements of their decor and planning features of the building are studied. It emphasizes the importance of preserving a unique example of quality architecture of the early twentieth century. The methodological basis of the study is to systematize and analyze the data obtained from various information sources. The article can be useful for historians of architecture or medicine, as well as for architects who have a scientific interest or work directly with cultural heritage sites. During the study, it was found that the current emergency condition of the building has been present for more than twenty years. Inattention to the unique architectural monument in the Main Directorate for the Protection of Cultural Heritage is explained by the lack of funds for restoration. Having a complicated history, more than a century-long, the estate is an example of successful planning of a medical institution of the early 20th century in the conditions of dense development in the central part of Kyiv.
FUNCTIONAL AND PLANNING ORGANIZATION OF A SHARED ACCOMMODATION CENTRE FOR THE ELDERLY AND ORPHANS
Authors: Obynochna Zoriana
Published: June 2022

The relevance of the research topic is related to the social need to establish a new type of institution, its main purpose is to bring older people and orphans together in the same environment.
Recommendations on the functional and planning organization of the centre for the elderly and orphans as a structural model, including an entrance and administrative areas, living areas for each age group, food, household, technical, rehabilitation, sports, educational and creative areas are presented.
Development such functionally new shared facilities for orphans and the elderly encourages architects and designers to get new and creative solutions for the community well-being.
The purpose of the study is to focus on the establishment of such centres for the joint temporary stay of orphans of all ages living in residential institutions and for the elderly in nursing homes, and to provide a functional pattern of this type of institution.
The study results can be applied to the design of such institutions in Ukraine.