bluuebunny/crossref_metadata_2025 huggingface dataset:
Short-Term Prognosis of Patients Hospitalized for Status Epilepticus in Ouagadougou, Burkina Faso
Authors: Labodi Lompo Djingri
Published: May 2022

Introduction: Status epilepticus is one of the most common neurological emergency, with high morbidity and mortality and an often poor functional prognosis in survivors. We carried out the present study, to describe the intra-hospital clinical course and to identify the risk factors for intra-hospital death of patients hospitalized for status epilepticus in Ouagadougou, Burkina Faso. Patients and methods: it was a prospective, cross-sectional, multi-center hospital, descriptive and analytical study, which took place from January 1, 2015 to December 31, 2019, involving patients consecutively hospitalized in the university hospitals of Ouagadougou, for status epilepticus. Sociodemographic characteristics, clinical data on admission, biological assessment on admission, EEG characteristics, brain scan and / or brain MRI results ; etiological diagnosis of status epilepticus and intra hospital evolutionary data of the patients, have been analyzed. Univariate analysis between the general characteristics of patients and the intra-hospital mortality, was performed in order to identify the risk factors for the intrahospital mortality. Results: The mean age of the patients was 36.6 years with an M / F sex ratio of 1.4 ; 66 patients (72.5%) had no clinical history of epilepsy, while 25 patients (27.5%) were already known to have epilepsy. The generalized tonic-clonic SE immediately (50.5%) and the focal secondarily generalized convulsive status epilepticus (29.7%) were the most common seizure types. The average duration of an SE episode was 18 hours. status epilepticus were subdivided into status epilepticus symptomatic of acute brain conditions with 61 cases (67%), dominated by central nervous system infections and acute strokes, and status epilepticus of non-acute or sequelae etiologies with 30 cases (33%), dominated by the sequelae of head trauma. Intra-hospital complications were dominated by prolonged post-critical mental confusion, 45 cases (49.4%) and aspiration pneumonia, 30 cases (33%). In-hospital mortality was 12.1% (11 patients). At the end of hospitalization, 49 patients (53.9%) still had moderate to severe disabilities. In univariate analysis, comatose non convulsive status epilepticus (p = 0.003), and altered consciousness on admission (p = 0.026), were the risk factors for in-hospital mortality. Conclusion: Prognosis of status epilepticus in Burkina Faso remains unfavorable with early mortality in more than one in 10 patients and poor functional outcome in more than half of the patients. Altered consciousness on admission and non-convulsive comatose status epilepticus were risk factors for early mortality. The fight against infectious diseases, the prevention of vascular risk factors, the promotion of helmet wearing in cyclists and motorcyclists, early admission of patients sufferinf of status epilepticus, and adequate and standardized management of status epilepticus, will help reduce the frequency and severity of this disease in our African regions.
There is one Cause for Mental illnesses
Authors: Coney Keith
Published: May 2022

Retired Admiral William H McRaven said in a 2014 Commencement Speech: “Here are the … lessons I learned from basic seal training that hopefully will be of value to you as you move forward in life. Every morning in seal training my instructors who were all Vietnam veterans would …. inspect my bed….. It was a simple task, mundane at best, but every morning we were required to make our bed to perfection.
Health Status of Young Girls in Selected Area of Bangladesh
Authors: Haque Tahmina , Rahman Tanzila , Islam Shiplu Mohammad Tauhidul , Haque Ahshadul , Begum Shirina , Rahman Mahbuba , Haque Imran
Published: May 2022

Background:Adolescence, a period of transition between childhood and adulthood, occupies a crucial position in the life of human beings. Hence, it is essential to improve health status through interventions. Objective:To assess and compare nutritional status of adolescent school girls in nutritional intervention and non-intervention area. Methods: A cross-sectional analytic study was conducted at Laxmipur sadar upazila as nutrition intervention area & neighboring Chatkhil upazila as non–nutrition intervention area. A total of 367 adolescent girls of age 10-19 years were selected purposively of them 177 and 190 were selected from intervention and non-intervention area respectively. Anthropometric data of the study subjects were collected by using standard techniques. Body mass index (BMI) and anemia were classified according to WHO cut off levels. Results:Study reveals that hemoglobin status was 72.3% normal, 20.3% mild anemia and 7.3% moderate anemia in intervention area and 51.6% normal, 43.7% mild anemia and 4.7% moderate anemia in non-intervention area. Significant difference was found both BMI and hemoglobin status among intervention and non-intervention area. Significant difference was found between intervention and non-intervention area of different illness, typhoid and jaundice. Conclusion:This study concludes that health status was better in intervention area than non-intervention area so community-based intervention is effective for better health status of young girls.
Some Stress Aspects in the Human Organism
Authors: Vincze Janos , Vincze-Tiszay Gabriella
Published: May 2022

In the human organism, the stress is a perturbation. The existence of the perturbations imposes a permanent control of the way the exit size is realized, so that any deviation can be corrected. Stress represents a normal reaction of the organism which appears as a response to an aggression situation which requires an unusual and quick adaptation effort from the organism. Stress is a state of putting in alert, of mobilizing the forces of the organism in the occasion of an event which requires, in order to be kept under control, a big amount of energy in a very short time. This alert state or action preparation translated through physical and psychological manifestations. Psychical stressors are those which come into being independently from the man’s will and destroy – as social factors – psychic and organic components taking place in the response, the organism consequently get tired. During the harmonic life gradually all human psycho-organic components shall get exhausted. During the individual evolution, the immediate vicinity imparts the codex of the principles of the moral motions. This is also a matter of opinion a kind of scale of values, more one can say it is very favourable for the individual from the healthy-spiritual point of view, because they are hardly touched by the negative effect of stress usually people beyond the pale of the society, in straits to the periphery. The physical discomfort feeling with the concomitant psychical reaction is realized by the measure of the personality’s sensitiveness. The modeling method in biophysics consists in the negative inverse connection
Support of Inclusive Education in Kryvyi Rig
Authors: Шестопалова (Бондар) Катерина Миколаївна , Шестопалова Олена Петрівна
Published: May 2022

An analysis of the system of training, the implementation of a pilot project "SUPPORT OF INCLUSIVE EDUCATION IN KRYVYI RIG". The team that worked in project by GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH) create strategy for training teachers that include 6 modules: 1) regulatory and legislative framework for inclusive education; 2) inclusion ethics and philosophy; universal design and reasonable accommodation of educational space; 3) support team: interdisciplinary interation; algorithm of provision of psycho-pedagogical, corrective and development services; 4) individualization of the educational process; 5) competences of the teacher in inclusive education: strategies of teaching in inclusive education, method of collaborative learning, integration of technology into the discipline teaching methods, peculiarities of formation of mathematical concepts in children with special needs, difficulties with reading mastering and correction of dyslexia in children with special educational needs, correction and development of sense side of reading, development of intelligence of a child with SEN with the help of kinesiology methods, cooperation of teacher, psychologist and parents of a child with special educational needs, five levels can be associated with parents engagement; 6) work with children with behavior problems; resource room as the method of a child specific sensor needs satisfaction.
PENYULUHAN DAMPAK LIMBAH BAHAN PLASTIK DAN PEMANFAATANNYA SEBAGAI USAHA PENGENDALIAN PENCEMARAN LINGKUNGAN
Authors: Sujarta Puguh
Published: May 2022

Environmental pollution occurs because of lack of knowledge of the environment of the community. Habit of throwing plastic garbage cans to make an impact for human life. The plastic waste is not easily degraded by decomposing animals. The amount of plastic waste can be hazardous to the environment and public health. Therefore, the need of public awareness of plastic waste is not his to control environmental pollution. The purpose of the implementation of the service activity is shown to explain to the concerns about the dangers of plastic waste to health and the environment; The second is to make some crafts of plastic waste materials. Activities that do on Saturday, October 15th, 2016 at SMP Depapre, Jayapura. The audience is 40 students. Using speech and simulation methods. The results showed that the activities of participants in the activities with enthusiastic and understand about the hazard of plastic waste. Keywords: plastic waste, impact, polluiton, environment
PEMBUATAN ALAT PENGHASIL BIOGAS SEDERHANA DI KAMPUNG HAWAI KABUPATEN JAYAPURA
Authors: Salim Ilham , Kafiar Frans
Published: May 2022

Biogas is a gas produced from the process of decomposition of organic materials by microorganisms in rare oxygen (anaerobic) conditions. Biogas component: ± 60% CH (methane), ± 38% CO (carbon dioxide), ± 2% N2 , O2 , H2 , and H2 S2. Biogas materials in this service comes from cow dung. Cow manure is a substrate that is considered most suitable as a source of biogas, because the substrate already contains methane as source of energy. In addition to cattle dung biogas can also reduce environmental pollution because it produced a more environmentally friendly energy source. In Kampung Hawai, Jayapura Regency, some of people have been doing cattle ranching activities. The waste in the form of fresh cow dung has not been utilized for the manufacture of biogas as an alternative energy source.The purpose of this devotional activity was to utilize fresh cow dung as a biogas energy source by creating simple biogas generator tools with cheap and easy equipment. The method used with the ratio of cow dung and water, 1:1 and also the addition of EM4 (Effective microorganisms) in the mixture of 5%, 7.5%, 10%; and 12.5% with fixed volume in the digester. The results of this activity obtained biogas which can be made by using a simple tool with respect to the ratio of mixture cow dung and water. Addition of EM4 affects the fermentation reaction in the digester to produce biogas. The highest biogas production was obtained in the addition of EM4 by 10% with the highest produced pressure and obtained quite significantly starting on the 12th day. The cattle ranchers at this location was interested in this devotion activity and will continue to apply the technology of making biogas that has been informed and understood. Keywords: Biogas, Cow Manure, EM4, Pressure
IDENTIFICATION OF CONCEPT UNDERSTANDING AND SELF EFFICACY ATOMIC STRUCTURE AND PERIODIC SYSTEM OF ELEMENTS
Authors: Virgianti Sri H Astuti , Nurwahyuni Nurwahyuni , Afadil Afadil , Mustapa Kasmudin
Published: May 2022

Concept understanding is a process in which students are able to understand the information obtained, both the definition, nature and description of a concept so that they are able to construct the concept. Self efficacy is the individual's ability to organize the actions needed for certain achievements. This study aims to (1) describe students' understanding of concepts on the material atomic structure and the periodic system of elements. (2) describe students' self-efficacy on the material on atomic structure and the periodic system of elements. The type of research used in this research is descriptive research with a quantitative approach. The instrument used in this study was a three-tier question and a self-efficacy questionnaire.This research was conducted at SMAN 4 Palu in class X MIPA. The results showed that the students' understanding of concepts in the atomic structure and the periodic system of elements, the average percentage of students understanding concepts was 34.35% belonging to the low category of concept understanding, 24.1% of students who did not understand the concept of low category while students who experienced a misconception of 41.35% in the sufficient category. The results of the student self-efficacy research show that students' self-efficacy is good because most of them are in the high category of 45 students (75%), sufficient category is 15 students (25%).
A Lightweight and Interpretable Model to Classify Bundle Branch Blocks from ECG Signals
Authors: Turbé Hugues , Bjelogrlic Mina , Namdar Mehdi , Gaudet-Blavignac Christophe , Zaghir Jamil , Goldman Jean-Philippe , Lokaj Belinda , Lovis Christian
Published: May 2022

Automatic classification of ECG signals has been a longtime research area with large progress having been made recently. However these advances have been achieved with increasingly complex models at the expense of model’s interpretability. In this research, a new model based on multivariate autoregressive model (MAR) coefficients combined with a tree-based model to classify bundle branch blocks is proposed. The advantage of the presented approach is to build a lightweight model which combined with post-hoc interpretability can bring new insights into important cross-lead dependencies which are indicative of the diseases of interest.
An Image Based Object Recognition System for Wound Detection and Classification of Diabetic Foot and Venous Leg Ulcers
Authors: Hüsers Jens , Moelleken Maurice , Richter Mats L. , Przysucha Mareike , Malihi Leila , Busch Dorothee , Götz Nina-Alexandra , Heggemann Jan , Hafer Guido , Wiemeyer Stefan , Babitsch Birgit , Heidemann Gunther , Dissemond Joachim , Erfurt-Berge Cornelia , Hübner Ursula
Published: May 2022

Venous leg ulcers and diabetic foot ulcers are the most common chronic wounds. Their prevalence has been increasing significantly over the last years, consuming scarce care resources. This study aimed to explore the performance of detection and classification algorithms for these types of wounds in images. To this end, algorithms of the YoloV5 family of pre-trained models were applied to 885 images containing at least one of the two wound types. The YoloV5m6 model provided the highest precision (0.942) and a high recall value (0.837). Its mAP_0.5:0.95 was 0.642. While the latter value is comparable to the ones reported in the literature, precision and recall were considerably higher. In conclusion, our results on good wound detection and classification may reveal a path towards (semi-) automated entry of wound information in patient records. To strengthen the trust of clinicians, we are currently incorporating a dashboard where clinicians can check the validity of the predictions against their expertise.
Can Artificial Intelligence Enable the Transition to Electric Ambulances?
Authors: Rigas Emmanouil S. , Billis Antonis , Bamidis Panagiotis D.
Published: May 2022

The electrification of the transportation sector is seen as a main pathway to reduce CO2 emissions and mitigate the earth’s climate change. Currently, Electric Vehicles (EVs) are entering the market fast. Although EVs have not been used as ambulances yet, the transition to the new type of vehicle is a matter of time. Thus, in this paper we discuss a number of research questions related to the efficient deployment of electric ambulances, focusing on the Artificial Intelligence (AI) point of view and we propose a framework for developing online algorithms that schedule the charging of electric ambulances and their assignment to patients.
Machine Learning in Medicine: To Explain, or Not to Explain, That Is the Question
Authors: Bousquet Cedric , Beltramin Diva
Published: May 2022

In 2022, the Medical Informatics Europe conference created a special topic called “Challenges of trustable AI and added-value on health” which was centered around the theme of eXplainable Artificial Intelligence. Unfortunately, two opposite views remain for biomedical applications of machine learning: accepting to use reliable but opaque models, vs. enforce models to be explainable. In this contribution we discuss these two opposite approaches and illustrate with examples the differences between them.
Physiotherapists’ Views on the Software Monitoring Application of a Wearable Assistive Glove
Authors: Bartali Valentina , Bulsink Vera
Published: May 2022

The FutureGlove project aims to further develop the CarbonHand system (a wearable assistive glove) by introducing a new software monitoring application. Within this study, we consulted five physiotherapists during online sessions to gain their views on use of data and patients’ empowerment. These first insights suggested that more data needs to be collected than it is doing now to monitor the patients’ progress, that therapists would like to personalize the amount of freedom they provide to their patients, and that they would like decision support for algorithms, but they do not fully trust them.
Implementing a Microservices Architecture for Predicting the Opinion of Twitter Users on COVID Vaccines
Authors: Guerdoux Guillaume , Audeh Bissan , Tiffet Théophile , Bousquet Cédric
Published: May 2022

A strong trend in the software industry is to merge the activities of deployment and operationalization through the DevOps approach, which in the case of artificial intelligence is called Machine Learning Operations (MLOps). We present here a microservices architecture containing the whole pipeline (frontend, backend, data predictions) hosted in Docker containers which exposes a model implemented for opinion prediction in Twitter on the COVID vaccines. This is the first description in the literature of implementing a microservice architecture using TorchServe, a library for serving Pytorch models.
Reliability of Drug-Drug Interaction Measurement on Real-Word Data: The ReMIAMes Project
Authors: Duclos Catherine , Griffon Nicolas , Daniel Christel , Bouzillé Guillaume , Delamarre Denis , Darmoni Stefan , Toubiana Laurent , Grosjean Julien
Published: May 2022

The ReMIAMes project proposes a methodological framework to provide a reliable and reproducible measurement of the frequency of drug-drug interactions (DDI) when performed on real-world data. This framework relies on (i) a fine-grained and contextualized definition of DDIs, (ii) a shared minimum information model to select the appropriate data for the correct interpretation of potential DDIs, (iii) an ontology-based inference module able to handle missing data to classify prescription lines with potential DDIs, (iv) a report generator giving the value of the measurement and explanations when potential false positive are detected due to a lack of available data. All the tools developed are intended to be publicly shared under open license.
Deviation of Physiological from Chronological Age Is Associated with Health
Authors: Peretz Lin , Rappoport Nadav
Published: May 2022

Biological age may be of higher importance than chronological age, yet biological age is not trivial to estimate. This study presents a regression model to predict age using routine clinical tests like laboratory tests using the UK Biobank (UKBB) data. We run different machine learning regression models for this predictions task and compare their performance according to RMSE. The models were trained using data from 472,189 subjects aged 37–82 years old and 61 different laboratory tests results. Our chosen model was an XGboost model, which achieved an RMSE of 6.67 years. Subjects whose the model predicted to be younger than their actual age were found to be healthier as they had fewer diagnoses, fewer operations, and had a lower prevalence of specific diseases than age-matched controls. On the other hand, subjects predicted to be older than their chronological age had no significant differences in the number of diagnoses, number of operations, and specific diseases than age-matched controls.
Impact of Electronic Medical Records Systems in Reporting HIV Health Data Indicators in Kenya
Authors: Ngugi Philomena N. , Gesicho Milka B. , Babic Ankica
Published: May 2022

Electronic Medical Records Systems (EMRs) improve the quality of patient care and reduce medical errors. Nevertheless, their role in health data indicator reporting performance is unclear. We assessed reporting completeness and timeliness of HIV indicator data to the national aggregate reporting system, District Health Information Software 2 (DHIS2) in Kenya. We compared the reporting performance of facilities with and without EMRs implementation for the year 2013 as EMRs uptake was in progress. The comparative analysis involved 104 facilities implemented with and 152 without KenyaEMR system on three HIV programmatic areas. There were no statistically significant differences in performance regarding reporting completeness and timeliness by facilities with or without EMRs (p-values > 0.05 on all the three areas). The KenyaEMR system assessed in this study, therefore, cannot be associated with the transformed performance in reporting health indicators. This was probably due to the fact that the EMRs do not report electronically to DHIS2. Additional analysis can be conducted to compare reporting performance once data exchange functionality is fully established between KenyaEMR and DHIS2 systems.
Automated Coding in Case Mix Databases of Bacterial Infections Based on Antimicrobial Susceptibility Test Results
Authors: Spiga Radia , Calvier François-Elie , Carricajo Anne , Pozzetto Bruno , Trombert-Paviot Béatrice , Bousquet Cédric
Published: May 2022

Our objective was to improve the accuracy of bacteria and resistance coding in a hospital case mix database. Data sources consisted of 50,074 files on bacteriological susceptibility tests transmitted with the HPRIM protocol from laboratory management system to electronic health record of the University hospital of Saint Etienne in July 2017. An algorithm was implemented to detect susceptibility tests containing information corresponding to codes whose addition in the case mix database was susceptible to increase the severity level of a diagnosis related group. Among 132 hospital stays fulfilling the conditions, 27 were lacking bacteria and/or resistance codes, and the tariff was increased for 9 stays, with earnings of €54,612. Analyzing Antimicrobial susceptibility tests helps to improve clinical coding and optimize the financial gain.
Mapping of ICD-O Tuples to OncoTree Codes Using SNOMED CT Post-Coordination
Authors: Ohlsen Tessa , Kruse Valerie , Krupar Rosemarie , Banach Alexandra , Ingenerf Josef , Drenkhahn Cora
Published: May 2022

Around 500,000 oncological diseases are diagnosed in Germany every year which are documented using the International Classification of Diseases for Oncology (ICD-O). Apart from this, another classification for oncology, OncoTree, is often used for the integration of new research findings in oncology. For this purpose, a semi-automatic mapping of ICD-O tuples to OncoTree codes was developed. The implementation uses a FHIR terminology server, pre-coordinated or post-coordinated SNOMED CT expressions, and subsumption testing. Various validations have been applied. The results were compared with reference data of scientific papers and manually evaluated by a senior pathologist, confirming the applicability of SNOMED CT in general and its post-coordinated expressions in particular as a viable intermediate mapping step. Resulting in an agreement of 84,00 % between the newly developed approach and the manual mapping, it becomes obvious that the present approach has the potential to be used in everyday medical practice.
Pattern-Based Logical Definitions of Prenatal Disorders Grounded on Dispositions
Authors: El Ghosh Mirna , Ghazouani Fethi , Akan Elise , Charlet Jean , Dhombres Ferdinand
Published: May 2022

Biomedical ontologies define concepts having biomedical significance and the semantic relations among them. Developing high-quality and reusable ontologies in the biomedical domain is a challenging task. Pattern-based ontology design is considered a promising approach to overcome the challenges. Ontology Design Patterns (ODPs) are reusable modeling solutions to facilitate ontology development. This study relies on ODPs to semantically enrich biomedical ontologies by assigning logical definitions to ontological entities. Specifically, pattern-based logical definitions grounded on dispositions are given to prenatal disorders. The proposed approach is performed under the supervision of fetal domain experts.
Non-Fungible Tokens as a Mechanism for Representing Patient Consent
Authors: Cunningham James , Davies Nigel , Devaney Sarah , Holm Søren , Harding Mike , Neumann Victoria , Ainsworth John
Published: May 2022

In recent years we have seen the adoption of distributed ledger technology (DLT), originally the mechanism underpinning the operation of the Bitcoin crypto currency, across a wider range of technology sectors including healthcare. DLT allows for the design of informatics systems with the properties of immutability, security, and decentralization. One recent innovation in the space has been the specification and development of Non-Fungible Tokens (NFTs). NFTs are decentralized DLT-based records that represent ownership of a unique digital asset. The predominant current use case for NFTs has been in the representation and sale of digital artwork, however the features offered by NFTs, unique-ness, immutability, transferability, and verifiability, are directly applicable to the design of health informatics systems. In this paper we explore these properties and describe a reference architecture for using NFTs as a means of representing and transferring records of patient’s consent for medical data use.
WikiMeSH: Multi Lingual MeSH Translations via Wikipedia
Authors: Dusenne Mikaël , Billey Kévin , Desgrippes Florent , Benis Arriel , Darmoni Stéfan Jacques , Grosjean Julien
Published: May 2022

Objective: The aim of this paper is to propose an extended translation of the MeSH thesaurus based on Wikipedia pages. Methods: A mapping was realized between each MeSH descriptor (preferred terms and synonyms) and corresponding Wikipedia pages. Results: A tool called “WikiMeSH” has been developed. Among the top 20 languages of this study, seven have currently no MeSH translations: Arabic, Catalan, Farsi (Iran), Mandarin Chinese, Korean, Serbian, and Ukrainian. For these seven languages, WikiMeSH is proposing a translation for 47% for Arabic to 34% for Serbian. Conclusion: WikiMeSH is an interesting tool to translate the MeSH thesaurus and other health terminologies and ontologies based on a mapping to Wikipedia pages.
REDIRECT: Mapping Drug Prescriptions and Evidence from Biomedical Literature
Authors: Thiao Layel Bruno , Jouhet Vianney , Blin Guillaume , Diallo Gayo
Published: May 2022

To enhance their practice, healthcare professionals need to cross-link various usage recommendations provided by heterogeneous vocabularies that must be retrieved and integrated conjointly. This is the aim of the Knowledge Warehouse / K-Ware platform. It enables establishing relevant bridges between different knowledge sources (structured vocabularies, thesaurus, ontologies) expressed in the semantic web standard languages (i.e. SKOS, OWL, RDF). This poster presents the strategy applied in K-Ware to hide the different aspects of linking literals with medical entities encoded in these knowledge sources to fetch some publications abstracts from Pubmed.
An Adverse Drug Reaction Database for Clinical Use – Potential of and Difficulties with the Summary of Product Characteristics
Authors: Eiermann Birgit , Rodrigues Daniel , Cohen Paul , Gustafsson Lars L.
Published: May 2022

Adverse drug reactions (ADRs) for all drugs in Europe are described in the legally approved Summary of Product Characteristics (SmPC). An overview of all ADRs of the patients’ drug list can support healthcare staff to link patient symptoms to possible ADRs. We review the possibilities and challenges to extract ADR information from SmPCs and present the development of our semi-automated procedure for extraction of ADRs from the tabulated section of the SmPCs to create a database, named Bikt, which is regularly updated and used at point of care in Sweden. The existence of five major table formats for ADRs used in the SmPCs required the development of different parsing scripts. Manual checks for correctness for all content has to be performed. The quality of extraction was investigated for all SmPCs by measuring precision, recall and F1 scores (i.e. the weighted harmonic mean of precision and recall) and compared with other methods published. We conclude that it is possible to semi-automatically extract ADR information from SmPCs. However, clear technical and content guidelines and standards for ADR tables and terms from drug registration authorities would lead to improved extraction and usability of ADR information at point of care.
The Prediction of Functional Outcome After Microsurgical Treatment of Unruptured Intracranial Aneurysm Based on Machine Learning
Authors: Ishankulov Timur , Grebenev Fyodor , Strunina Uliya , Shekhtman Oleg , Eliava Shalva , Danilov Gleb
Published: May 2022

Our study aimed to create a machine learning model to predict patients’ functional outcomes after microsurgical treatment of unruptured intracranial aneurysms (UIA). Data on 615 microsurgically treated patients with UIA were collected retrospectively from the Electronic Health Records at N.N. Burdenko Neurosurgery Center (Moscow, Russia). The dichotomized modified Rankin Scale (mRS) at the discharge was used as a target variable. Several machine learning models were utilized: a random forest upon decision trees (RF), logistic regression (LR), support vector machine (SVM). The best result with F1-score metric = 0.904 was produced by the SVM model with a label-encode method. The predictive modeling based on machine learning might be promising as a decision support tool in intracranial aneurysm surgery.
Are Personal Health Records (PHRs) Facilitating Patient Safety? A Scoping Review
Authors: Joseph Amanda L. , Monkman Helen , Kushniruk Andre W. , Borycki Elizabeth M.
Published: May 2022

Personal Health Records (PHRs) are poised to improve patient safety, however the mechanism(s) in which they improve safety is not clear. To this end, we conducted a scoping review with the following objectives: 1) explore the extent of the evidence that PHRs improve patient safety, 2) determine where PHR research has been done per International Medical Informatics Association (IMIA) Represented Region [1], 3) to identify the PHR naming convention(s) used per IMIA Region [1]. The findings revealed that there is limited evidence that PHRs improve patient safety. The results also revealed heterogeneity in PHR nomenclature and how they were used in healthcare settings. However, the overarching theme of the study, was that future research is needed to ensure that PHRs are designed and used in a patient safety context with human factors and usability considerations.
Data Analytics of Electronic Medical Record to Study Racial Diversities in Cardiovascular Diagnosis and Treatment
Authors: Panahiazar Maryam , Chern Yorick , Riojas Ramon , Latif Omar S. , Hadley Dexter , Beygui Ramin E.
Published: May 2022

The study of precision medicine that measures the effects of social, cultural, and environmental influences on health is essential to improve health outcomes. Race is a social concept used historically to divide, track, control populations, and reinforce social hierarchies. Beyond genetics, race is also a surrogate for other socioeconomic factors affecting patient outcomes. Our data analytics study aims to analyze the Electronic Medical Record (EMR) to study patients of different races in diagnosing and treating Coronary Artery Disease (CAD). We found no race discrepancies at the University of California San Francisco Medical Centers. This study opens several new hypotheses for further research in this crucial field.
A Deep Learning Method for Automatic Identification of Drusen and Macular Hole from Optical Coherence Tomography
Authors: Pace Teresa , Degan Nicolò , Giglio Md Rosa , Tognetto Md Daniele , Accardo Agostino
Published: May 2022

Deep Learning methods have become dominant in various fields of medical imaging, including ophthalmology. In this preliminary study, we investigated a method based on Convolutional Neural Network for the identification of drusen and macular hole from Optical Coherence Tomography scans with the aim to assist ophthalmologists in diagnosing and assessing retinal diseases.
Design of a Patient-Accessible Electronic Health Record System in Mental Health
Authors: Hochwarter Stefan , Fehler Georgia , Muente Catharina , Eisenmann Yvonne , Heinze Martin , Hibsch Charline , Schwarz Julian
Published: May 2022

Patient accessible Electronic Health Records (PAEHRs) are increasingly implemented internationally. However, studies carried out in the mental health care setting report several practical and ethical challenges when introducing PAEHRs. In this paper we aim to explore the requirements of a PAEHR system in mental health. As part of a participatory design process, we collected qualitative data from service users and staff in a rural mental health day clinic setting, which can be summarized in the following themes: I) Function and way of the documentation; II) Impact on Treatment; III) Concerns about PAEHRs; IV) time of access to PAEHRs; V) Different views on what to share; VI) Access, Data Privacy and Special Features. Our study uncovered the complexity and special requirements and barriers to the design of PAEHR in mental health. While we are in an early stage of our study, we will continue this iterative process and adapt the PAEHR system to the specific needs of the users and domains.
Design for a Virtual Peer-to-Peer Knowledge to Action Platform for Type 2 Diabetes
Authors: Golkhandan Elham , Paglialonga Alessia , Guergachi Aziz , Lussier Marie-Therese , Richard Claude , Dube Laurette , Zenlea Ian , Kyba Robert , Mittal Manmohan , “Smokey” Thomas Warren , Keshavjee Karim
Published: May 2022

Many patients with Type 2 Diabetes (T2D) have difficulty in controlling their disease despite wide-spread availability of high-quality guidelines, T2D education programs and primary care follow-up programs. Current diabetes education and treatment programs translate knowledge from bench to bedside well, but underperform on the ‘last-mile’ of converting that knowledge into action (KTA). Two innovations to the last-mile problem in management of patients with T2D are introduced. 1) Design of a platform for peer-to-peer groups where patients can solve KTA problems together in a structured and psychologically safe environment using all the elements of the Action Cycle phase of the KTA framework. The platform uses Self-Determination Theory as the behavior change theory. 2) A novel patient segmentation method to enable the formation of groups of patients who have similar behavioral characteristics and therefore who are more likely to find common cause in the fight against diabetes.
An Agile Approach to Accelerate Development and Adoption of Electronic Product Information Standards
Authors: Chronaki Catherine , Anderson Craig , Villadsen Jens Kristian , Hurlen Petter , Cangioli Giorgio , Ferrari Giovanna Maria , Moen Anne
Published: May 2022

The Medical Product Information found in most medication boxes offer a wealth of information, including terms of active ingredients, excipients, indications, dosage, route of administration, risks, and safety information. Digital health services that help patients, their care givers, and health professionals to manage medication, can be improved with tailored information based on user profile, the patient’s Electronic Health Record (EHR) summary, and Medicinal Product Information. The electronic Product information (ePI) comprises the summary of product characteristics, package leaflet, and product label. The European Medicines Agency released in 2021 the first version of the EU proof-of-concept ePI standard based on HL7 FHIR. The Gravitate-Health project uses this common standard as a springboard to implement a federated open-source platform and services that helps advance access, understanding, and adherence by providing trusted medicinal information in an interoperable and scalable way. In this paper, we present the agile technical approach and co-creation process to design, test, and progressively mature interoperability working with the HL7 Vulcan Accelerator and FHIR connectathons.
Symptom-Based COVID19 Screening Model Combined with Surveillance Information
Authors: Lee Dohyung , Kim Myeongchan , Choo Hyunwoo , Shin Soo-Yong
Published: May 2022

As the number of cases for COVID-19 continues to grow unprecedentedly, COVID-19 screening is becoming more important. In this study, we trained machine learning models from the Israel COVID-19 dataset and compared models that used surveillance indices of COVID-19 and those that did not. The AUC scores were 0.8478±0.0037 and 0.8062±0.005 with and without surveillance information, respectively, and there was significant improvement when the surveillance information was used.
ECHO: An Information System for the Monitoring and Evaluation of Dental Student Activity in a Pre-Doctoral Clinic
Authors: Ballester Benoit , Bukiet Frédéric , Dufour Jean-Charles
Published: May 2022

The main goal of dental education is to develop health professionals who will maintain and improve the oral health of patients. This requires the quantitative and qualitative assessment of dental student activity. The aim of this work is to describe the ECHO information system that was developed at Timone Hospital (France) for the monitoring and evaluation of dental student activity and to present the results of a qualitative evaluation of student perceptions of this system. According to the analysis of the UML model of care-related procedures and data, the pre-existing process of student evaluation was characterized by redundancy between administrative and educational data. ECHO was developed in PHP/MySQL and designed to centralize the two types of data in a unified computerized process. The qualitative evaluation of dental student perceptions of ECHO was performed using an anonymous online Google Form questionnaire. Among the respondents (102/254 students), 96% stated that ECHO is easy to use, 86% that it saves time, and 81% that it gives them a better overview of their activity. After several years of use, ECHO has solved many of the difficulties related to the use of internship paper booklets, while also providing a documentary database of the activities of our dental department. The student activity data stored in ECHO are directly accessible by faculty members and can be reused to facilitate departmental management and research and to improve patient follow-up.
Artificial Intelligence Competencies in Postgraduate Medical Training in Germany
Authors: Agha-Mir-Salim Louis , Mosch Lina , Klopfenstein Sophie A.I. , Wunderlich Maximilian M. , Frey Nicolas , Poncette Akira-Sebastian , Balzer Felix
Published: May 2022

Routine medical care is to be transformed by the introduction of artificial intelligence (AI), requiring medical professionals to acquire a novel set of skills. We assessed the density of AI learning objectives and the availability of courses containing AI content in postgraduate medical education in Germany. The results reveal general paucity in AI learning objectives and content across (sub-)specialty training and continuing medical education (CME) in Germany. Innovative and regulatory solutions are needed to herald an era of physicians competent in navigating medical AI applications.
Assessment of the Body Posture of Interventional Radiologists
Authors: Lohmann Saskia , Öztürk Gürkan , Junger Denise , Hoffmann Rüdiger , Burgert Oliver
Published: May 2022

Physicians in interventional radiology are exposed to high physical stress. To avoid negative long-term effects resulting from unergonomic working conditions, we demonstrated the feasibility of a system that gives feedback about unergonomic situations arising during the intervention based on the Azure Kinect camera. The overall feasibility of the approach could be shown.
Evaluating mHealth Design for People with Dementia: Preliminary Results
Authors: Engelsma Thomas , Rippin Laila R. , Jaspers Monique W. , Peute Linda W.
Published: May 2022

The availability of mHealth for people with dementia is increasing. Various mHealth design guidelines for this population have been proposed. In this study, we developed a binary checklist with evaluation statements to assess the implementation of twenty design suggestions in seven currently available mHealth apps for people with dementia. Between 17%–65% of the evaluation statements in the checklist were implemented in these apps. Not all statements were considered applicable for each assessed mHealth app, which resulted in dividing the criteria in two groups as either key evaluation statements or optional evaluation statements. In future work we want to augment this checklist to contribute to the future design of mHealth for people with dementia.
Digital Health Education: Determining Competences and Piloting Innovative Study Course
Authors: Chaltikyan Georgi , Fernandes Fara Aninha , Pfeiffer Jishen
Published: May 2022

Digital technology for health services plays a critical role in the delivery of health services. In order to move towards universal healthcare, improvement of patient outcomes and better health, one must make use of the advantages of Digital Health tools and recognition of the role of the health ICT worker. Therefore, it is necessary to have a workforce that is competent to use these tools. Uniquely positioned at the intersection of healthcare and information technology, the domain of Digital Health builds on a variety of disciplines termed biomedical and health informatics, and other allied fields. With the increasing need to have a knowledgeable, skilled and competent workforce, it is necessary to concentrate efforts towards the provision of education modules in Digital Health. While continuing medical education, certificate courses and other similar courses attempt to bridge the gap in the delivery of Digital Health education, it is also paramount to establish dedicated and standalone courses. Streamlining approaches to Digital Health Education across disciplinary, cultural and national boundaries, is key to address the challenges of firmly embedding Digital Health courses in the fabric of university education. In the effort to provide the necessary knowledge, skills and competencies (KSCs) to the current health ICT worker, the Deggendorf Institute of Technology, European Campus Rottal-Inn (DIT-ECRI) is in the process of piloting a virtual course in Global Digital Health. With the ability to provide core competencies in Digital heath, this virtual course is a step towards advancing Global Digital Health Education.
Augmenting THerapeutic Effectiveness Through Novel Analytics (ATHENA) – A Public and Private Partnership Project Funded by the Flemish Government (VLAIO)
Authors: Petsophonsakul Ploingarm , Pirmani Ashkan , De Brouwer Edward , Akand Murat , Botermans Wouter , Van Der Aa Frank , Vermeesch Joris Robert , Offner Fritz , Wuyts Roel , Moreau Yves , Maes Ingrid , Blockx Ines , Van Rompuy Patricia , Lewi Martine , Vannieuwenhuyse Bart
Published: May 2022

The complexity and heterogeneity of cancers leads to variable responses of patients to treatments and interventions. Developing models that accurately predict patient’s care pathways using prognostic and predictive biomarkers is increasingly important in both clinical practice and scientific research. The main objective of the ATHENA project is to: (1) accelerate data driven precision medicine for two use cases – bladder cancer and multiple myeloma, (2) apply distributed and privacy-preserving analytical methods/ algorithms to stratify patients (decision support), (3) help healthcare professionals deliver earlier and better targeted treatments, and (4) explore care pathway automations and improve outcomes for each patient. Challenges associated with data sharing and integration will be addressed and an appropriate federated data ecosystem will be created, enabling an interoperable foundation for data exchange, analysis and interpretation. By combining multidisciplinary expertise and tackling knowledge gaps in ATHENA, we propose a novel federated privacy preserving platform for oncology research.
Enriching UMLS-Based Phenotyping of Rare Diseases Using Deep-Learning: Evaluation on Jeune Syndrome
Authors: Faviez Carole , Vincent Marc , Garcelon Nicolas , Michot Caroline , Baujat Genevieve , Cormier-Daire Valerie , Saunier Sophie , Chen Xiaoyi , Burgun Anita
Published: May 2022

The wide adoption of Electronic Health Records (EHR) in hospitals provides unique opportunities for high throughput phenotyping of patients. The phenotype extraction from narrative reports can be performed by using either dictionary-based or data-driven methods. We developed a hybrid pipeline using deep learning to enrich the UMLS Metathesaurus for automatic detection of phenotypes from EHRs. The pipeline was evaluated on a French database of patients with a rare disease characterized by skeletal abnormalities, Jeune syndrome. The results showed a 2.5-fold improvement regarding the number of detected skeletal abnormalities compared to the baseline extraction using the standard release of UMLS. Our method can help enrich the coverage of the UMLS and improve phenotyping, especially for languages other than English.
Analyzing the Information Content of Text-Based Files in Supplementary Materials of Biomedical Literature
Authors: Naderi Nona , Mottaz Anaïs , Teodoro Douglas , Ruch Patrick
Published: May 2022

We present an analysis of supplementary materials of PubMed Central (PMC) articles and show their importance in indexing and searching biomedical literature, in particular for the emerging genomic medicine field. On a subset of articles from PubMed Central, we use text mining methods to extract MeSH terms from abstracts, full texts, and text-based supplementary materials. We find that the recall of MeSH annotations increases by about 5.9 percentage points (+20% on relative percentage) when considering supplementary materials compared to using only abstracts. We further compare the supplementary material annotations with full-text annotations and we find out that the recall of MeSH terms increases by 1.5 percentage point (+3% on relative percentage). Additionally, we analyze genetic variant mentions in abstracts and full-texts and compare them with mentions found in supplementary text-based files. We find that the majority (about 99%) of variants are found in text-based supplementary files. In conclusion, we suggest that supplementary data should receive more attention from the information retrieval community, in particular in life and health sciences.