Empowering healthcare education: A multilingual ontology for medical informatics and digital health (MIMO) integrated to artificial intelligence powered training in smart hospitals.

Objective: A comprehensive understanding of professional and technical terms is essential to achieving practical results in multidisciplinary projects dealing with health informatics and digital health. The medical informatics multilingual ontology (MIMO) initiative has been created through international cooperation. MIMO is continuously updated and comprises over 3700 concepts in 37 languages on the Health Terminology/Ontology Portal (HeTOP). Methods: We conducted case studies to assess the feasibility and impact of integrating MIMO into real-world healthcare projects. In HosmartAI, MIMO is used to index technological tools in a dedicated marketplace and improve partners' communication. Then, in SaNuRN, MIMO supports the development of a "Catalog and Index of Digital Health Teaching Resources" (CIDHR) backing digital health resources retrieval for health and allied health students. Results: In HosmartAI, MIMO facilitates the indexation of technological tools and smooths partners' interactions. In SaNuRN within CIDHR, MIMO ensures that students and practitioners access up-to-date, multilingual, and high-quality resources to enhance their learning endeavors. Conclusion: Integrating MIMO into training in smart hospital projects allows healthcare students and experts worldwide with different mother tongues and knowledge to tackle challenges facing the health informatics and digital health landscape to find innovative solutions improving initial and continuous education.

In Silico Screening of Phytocompounds from West African Traditional Medicine and Molecular Docking Targeting Dengue Virus Protein NS2B/NS3.

Traditional medicine offers a wide range of application for in silico study techniques. This drug research and development strategy is embryonic in the West African context, particularly in Burkina Faso, which is increasingly faced with emerging diseases such as dengue fever. Circulation of the 4 serotypes of this virus has been documented in the country. This study aims to evaluate the therapeutic potential of phytocompounds contained in the West African pharmacopoeia against dengue virus NS2B/NS3 protein, using computational methods integrating several software packages and databases. Based on a literature review, we identified 191 molecules from 30 plants known for their antiviral effects. Five met the inclusion criteria for molecular docking: patulin from calotropis procera, resiniferonol from Euphorbia poissonii, Securinol A from Flueggea virosa, Shikimic acid and Methyl gallate from Terminalia macroptera. The best binding scores were observed between resiniferonol and the serotypes 1, 2 and 4 NS2B/NS3 protease, with binding energies of -7.4 Kcal/mol, -6.8 Kcal/mol and -7.3 Kcal/mol respectively; while the NS2B/NS3 protease of serotype 3 had the best affinity for securinol A (-7 Kcal/mol). This study points the way to further research in computer aided drug design field and calls for multidisciplinary collaboration to promote West African medicinal plants against health challenges.

Advancing CPR Training with Virtual Reality: A Review.

This literature review assesses the effectiveness of virtual reality (VR) serious games in cardiopulmonary resuscitation training, focusing on its impact on skill acquisition, confidence, and knowledge retention.

Design and Integration of an Intelligent Agent to a Telemedicine Platform, for the Translation of Exchanges Between Doctor and Patient During Teleconsultation: Methodology of Design and Technological Choices.

After having designed and implemented a telemedicine solution equipped with a video presence tool for teleconsultation and tele-expertise and in order to obtain a faithful communication between healthcare professional and patient despite language differences, our study was to perform a literary review on the various existing works and to perform analysis on the different types of neural network for designing an voice intelligent agent for translation during exchanges between doctor and patient during teleconsultation and make tool choices for its development.

Artificial Intelligence System for Automated Breast Cancer Detection in Pathology in Burkina Faso: Methodology Overview.

The introduction of artificial intelligence (AI) in breast cancer diagnosis in Burkina Faso represents a significant advancement in the field of healthcare. Faced with the public health issue posed by breast cancer, this study focuses on the use of AI to improve early and accurate detection of this disease from histopathological images. For the implementation of the system, we utilized a customized architecture tailored to our context where image quality is low, based on the convolutional neural networks algorithm from the Keras library of TensorFlow. Subsequently, we developed a platform to facilitate its use. This article aims to present the methodology that was used and the results obtained.

Comparative Analysis of Artificial Intelligence Algorithms for Breast Cancer Detection from Pathological Image in Burkina Faso.

Artificial Intelligence (AI) has revolutionized many fields, including medical imaging. This revolution has enabled the digitization of medical images, the development of algorithms allowing the use of data captured in natural language, and deep learning, enabling the development of algorithms for automatic processing of medical images from massive medical data. In Burkina Faso, early and accurate detection of breast cancer is a significant challenge due to limited resources and lack of specialized expertise. In this article, we examine the effectiveness of different artificial intelligence algorithms for breast cancer detection from pathological image.

Digital Health Education for the Future: The SaNuRN (Santé Numérique Rouen-Nice) Consortium's Journey.

SaNuRN is a five-year project by the University of Rouen Normandy (URN) and the Côte d'Azur University (CAU) consortium to optimize digital health education for medical and paramedical students, professionals, and administrators. The project includes a skills framework, training modules, and teaching resources. In 2027, SaNuRN is expected to train a significant portion of the 400,000 health and paramedical professions students at the French national level. Our purpose is to give a synopsis of the SaNuRN initiative, emphasizing its novel educational methods and how they will enhance the delivery of digital health education. Our goals include showcasing SaNuRN as a comprehensive program consisting of a proficiency framework, instructional modules, and educational materials and explaining how SaNuRN is implemented in the participating academic institutions. SaNuRN is a project aimed at educating and training health-related and paramedics students in digital health. The project results from a cooperative effort between URN and CAU, covering four French departments. The project is based on the French National Referential on Digital Health (FNRDH), which defines the skills and competencies to be acquired and validated by every student in the health, paramedical, and social professions curricula. The SaNuRN team is currently adapting the existing URN and CAU syllabi to FNRDH and developing short-duration video capsules of 20 to 30 minutes to teach all the relevant material. The project aims to ensure that the largest student population earns the necessary skills, and it has developed a two-tier system involving facilitators who will enable the efficient expansion of the project's educational outreach and support the students in learning the needed material efficiently. With a focus on real-world scenarios and innovative teaching activities integrating telemedicine devices and virtual professionals, SaNuRN is committed to enabling continuous learning for healthcare professionals in clinical practice. The SaNuRN team introduced new ways of evaluating healthcare professionals by shifting from a knowledge-based to a competencies-based evaluation, aligning with the Miller teaching pyramid and using the Objective Structured Clinical Examination and Script Concordance Test in digital health education. Drawing on the expertise of URN, CAU, and their public health and digital research laboratories and partners, the SaNuRN project represents a platform for continuous innovation, including telemedicine training and living labs with virtual and interactive professional activities. The SaNuRN project provides a comprehensive, personalized 30-hour training package for health and paramedical students, addressing all 70 FNRDH competencies. The program is enhanced using AI and NLP to create virtual patients and professionals for digital healthcare simulation. SaNuRN teaching materials are open-access. The project collaborates with academic institutions worldwide to develop educational material in digital health in English and multilingual formats. SaNuRN offers a practical and persuasive training approach to meet the current digital health education requirements.

Sharing Digital Health Educational Resources in a One-Stop Shop Portal: Tutorial on the Catalog and Index of Digital Health Teaching Resources (CIDHR) Semantic Search Engine.

BACKGROUND: Access to reliable and accurate digital health web-based resources is crucial. However, the lack of dedicated search engines for non-English languages, such as French, is a significant obstacle in this field. Thus, we developed and implemented a multilingual, multiterminology semantic search engine called Catalog and Index of Digital Health Teaching Resources (CIDHR). CIDHR is freely accessible to everyone, with a focus on French-speaking resources. CIDHR has been initiated to provide validated, high-quality content tailored to the specific needs of each user profile, be it students or professionals. OBJECTIVE: This study's primary aim in developing and implementing the CIDHR is to improve knowledge sharing and spreading in digital health and health informatics and expand the health-related educational community, primarily French speaking but also in other languages. We intend to support the continuous development of initial (ie, bachelor level), advanced (ie, master and doctoral levels), and continuing training (ie, professionals and postgraduate levels) in digital health for health and social work fields. The main objective is to describe the development and implementation of CIDHR. The hypothesis guiding this research is that controlled vocabularies dedicated to medical informatics and digital health, such as the Medical Informatics Multilingual Ontology (MIMO) and the concepts structuring the French National Referential on Digital Health (FNRDH), to index digital health teaching and learning resources, are effectively increasing the availability and accessibility of these resources to medical students and other health care professionals. METHODS: First, resource identification is processed by medical librarians from websites and scientific sources preselected and validated by domain experts and surveyed every week. Then, based on MIMO and FNRDH, the educational resources are indexed for each related knowledge domain. The same resources are also tagged with relevant academic and professional experience levels. Afterward, the indexed resources are shared with the digital health teaching and learning community. The last step consists of assessing CIDHR by obtaining informal feedback from users. RESULTS: Resource identification and evaluation processes were executed by a dedicated team of medical librarians, aiming to collect and curate an extensive collection of digital health teaching and learning resources. The resources that successfully passed the evaluation process were promptly included in CIDHR. These resources were diligently indexed (with MIMO and FNRDH) and tagged for the study field and degree level. By October 2023, a total of 371 indexed resources were available on a dedicated portal. CONCLUSIONS: CIDHR is a multilingual digital health education semantic search engine and platform that aims to increase the accessibility of educational resources to the broader health care-related community. It focuses on making resources "findable," "accessible," "interoperable," and "reusable" by using a one-stop shop portal approach. CIDHR has and will have an essential role in increasing digital health literacy.

Consumer Informatics and One Health: Shifting the Focus from the Individual to the Globe. Findings from the Yearbook 2023 Section on Education and Consumer Health Informatics.

OBJECTIVE: To summarise the state of the art during the year 2022 in consumer health informatics and education, with a special emphasis on "One Health". METHODS: We conducted a systematic search of articles published in PubMed. We build queries to merge terms related to "consumer health informatics", "one health", and "digital". We retrieved 94 potential articles for review. These articles were screened according to topic relevance and 12 were selected for consideration of best paper candidates, which were then presented to a panel of international experts for full paper review and scoring. The top five papers were discussed in a consensus meeting. Three papers received the highest score from the expert panel, and these papers were selected to be representative papers on consumer informatics for exploring one health from consumer perspective in the year 2022. RESULTS: Bibliometrics analysis conducted on words found in abstracts of the 12 candidate papers revealed four clusters of articles, where clustering outcomes explained 96.91% of the dispersion. The first cluster composes three papers related to patient engagement in primary care practices, using digital-delivered diabetes prevention programmes, or exploring citizen involvement in co-designing environmental projects (such as air pollution exposure and health). The second cluster represents four papers related to digital health literacy and consumer behavior, such as digital vaccine literacy, and food labelling influences and whether displaying Nutri- and Eco-Score at food product level led to improved consumer choices. The third cluster consists of two papers exploring strategies to involve citizens in various science projects while analyzing the quality of citizen-collected data (e.g., mosquito bites or gastropod community dataset). The last cluster contains three papers related to the relationships between human behavior with their environment and their contribution to citizen science projects (e.g., biological water quality in the Netherlands distribution, composition, abundance of debris across sandy beaches in Australia and its regions, urbanization and reptile biodiversity across Florida). CONCLUSION: Traditionally, consumer health informatics focuses on providing individuals with tools and resources to actively manage their own health. By incorporating a global health (or one health) perspective, our field is now at a crossroad, demanding us to think beyond the individual and challenging us to instill the thinking that our actions not only have consequences on the individual but also on the population and the environment. Perhaps this is also a reflective time for the consumer informatics field, to consider shifting the focus from the individual to one that is more aligned with one health, helping consumers gain awareness of how their actions impact on the individual, the population and the environment, and providing them with tools to work collectively to help decide how their actions may bring benefits (as well as harms) across these levels.

Setting up a Video Transmission Tool for Teleconsultation and Tele-Expertise in an African Context: Case of Burkina Faso.

Since the COVID-19 health crisis, telemedicine has received a lot of attention around the world. Following attempts to set up a telemedicine system, in particular teleconsultation and teleexpertise, which proved inconclusive in Burkina, we have seen several technologies and tools that could enable the implementation of a telemedicine solution that meets the realities of Burkina Faso. The results of the study of the existing system and interviews with health professionals have made it possible to design a telemedicine platform combining a scalable video-transmission tool adapted to the country's health system.

The EPIDIA4Kids protocol for a digital epidemiology study on brain functioning in children, based on a multimodality biometry tool running on an unmodified tablet.

Introduction: Neurodevelopment and related mental disorders (NDDs) are one of the most frequent disabilities among young people. They have complex clinical phenotypes often associated with transnosographic dimensions, such as emotion dysregulation and executive dysfunction, that lead to adverse impacts in personal, social, academic, and occupational functioning. Strong overlap exists then across NDDs phenotypes that are challenging for diagnosis and therapeutic intervention. Recently, digital epidemiology uses the rapidly growing data streams from various devices to advance our understanding of health's and disorders' dynamics, both in individuals and the general population, once coupled with computational science. An alternative transdiagnostic approach using digital epidemiology may thus better help understanding brain functioning and hereby NDDs in the general population. Objective: The EPIDIA4Kids study aims to propose and evaluate in children, a new transdiagnostic approach for brain functioning examination, combining AI-based multimodality biometry and clinical e-assessments on an unmodified tablet. We will examine this digital epidemiology approach in an ecological context through data-driven methods to characterize cognition, emotion, and behavior, and ultimately the potential of transdiagnostic models of NDDs for children in real-life practice. Methods and analysis: The EPIDIA4Kids is an uncontrolled open-label study. 786 participants will be recruited and enrolled if eligible: they are (1) aged 7 to 12 years and (2) are French speaker/reader; (3) have no severe intellectual deficiencies. Legal representative and children will complete online demographic, psychosocial and health assessments. During the same visit, children will perform additionally a paper/pencil neuro-assessments followed by a 30-min gamified assessment on a touch-screen tablet. Multi-stream data including questionnaires, video, audio, digit-tracking, will be collected, and the resulting multimodality biometrics will be generated using machine- and deep-learning algorithms. The trial will start in March 2023 and is expected to end by December 2024. Discussion: We hypothesize that the biometrics and digital biomarkers will be capable of detecting early onset symptoms of neurodevelopment compared to paper-based screening while as or more accessible in real-life practice.

Consuming Health Information and Vulnerable Populations: Factors of Engagement and Ongoing Usage.

OBJECTIVES: To summarise the state of the art during the year 2021 in consumer health informatics and education, with a special emphasis on "Inclusive Digital Health: Addressing Equity, Literacy, and Bias for Resilient Health Systems". METHODS: We conducted a systematic search of articles published in PubMed using a predefined set of queries. In order to build queries, we have used a common understanding of digital inclusion. Leaving no one behind in the digital age requires not only reaching the most vulnerable populations, but also those people and population groups that are not digitally literate. It implies appropriate access, digital skills, and usability and navigability aspects in the development of technological solutions. Thus, we identified 126 potential articles for review. These articles were screened according to topic relevance and 13 were selected for consideration of best paper candidates, which were then presented to a panel of international experts for full paper review and scoring. The top five papers were discussed in a consensus meeting. Four papers received the highest score from the expert panel, and these papers were selected to be representative papers on consumer informatics for exploring inclusive digital health in the year 2021. RESULTS: Bibliometrics analysis conducted on words found in abstracts of the candidate papers revealed five clusters of articles, where the clustering outcomes explained 93.58% of the dispersion. The first cluster analysed the use of mobile apps to improve quality of communications between racial subgroups (e.g., Black patients and their family members) and healthcare professionals, and reduce racial disparities in core palliative care outcomes. The second cluster revealed studies reporting health literacy and experience of patients with specific diseases or impairments (e.g., type 2 diabetes, asthma and deaf people). The third focused assessing the effectiveness of interactive social media interventions on changing health behaviors, health outcomes and health equity in the adult population. The fourth targeted people with limited health literacy, as well as potentially disadvantaged or marginalized groups (people with cerebrovascular or cancer problems, students with mental problems, African American Young adults), and explored how social media may help reduce health disparities and improve health outcomes. The last explored health literacy levels among groups who experience difficulties with health service engagement and retention (patients with cancer or lay consumers of online disease information). CONCLUSIONS: Although the query was built to address consumer inclusiveness and digital health, without specifying any health status or disease, COVID-19 was the topic in a lot of retrieved papers. Beyond the classic health issues targeted by social media (e.g., influencing health behaviors, from smoking and diet adherence to preventative screening and exercise habits), the pandemic has exposed many situations of vulnerability and health inequality. There is universal agreement on the necessity of a healthcare policy that addresses issues of gender, age, sexual orientation, and different cultures to ensure health equity for all, regardless of age or resources available. The place of digital health is studied both as a solution and a possible factor of accentuating healthcare disparities, inequalities, and exclusions. Healthcare providers should implement a digital health literacy plan to make sure health information technology is an option for everyone. Public health policies and health promotion strategies must focus on strengthening and adapting the digital health literacy in known vulnerable subgroups (ethnic and racial minorities, sexual and gender minorities, children and adolescents, elderly people, students population, impaired people, patients with cancer and chronic diseases) increasing citizen technology engagement and guaranteeing equity in access to information and in the skills to manage, discriminate, and apply information to health.

Management of Patients with Diabetic Macular Edema Switched from Dexamethasone Intravitreal Implant to Fluocinolone Acetonide Intravitreal Implant.

To assess anatomical and functional outcomes after switching from dexamethasone implant (DEXi) to fluocinolone acetonide implant (FAci) in 113 diabetic macular edema eyes, a multicentric retrospective observational study was conducted. Seventy-five eyes (73.5%) were switched 1−8 weeks after their last DEXi. The mean best-corrected visual acuity improved to 59.8 letters at month 4 and remained stable during the follow-up. The mean central macular thickness (CMT) significantly decreased during the follow-up, with a minimum of 320.9 µm at month 3. The baseline CMT was higher in eyes that received the last DEXi >8 weeks versus <8 weeks before the first FAci (p < 0.021). After FAci injection, additional treatments were needed in 37 (32.7%) eyes. A longer diabetes duration (p = 0.009), a longer time between the last DEXi and the first FAci (p = 0.035), and a high baseline CMT (p = 0.003) were risk factors for additional treatments. The mean intraocular pressure was <19 mmHg at all timepoints, with no difference between eyes receiving the last DEXi ≤8 weeks or >8 weeks before the switch. Switching from DEXi to FAci in DME is effective and safe. A short time between the last DEXi and the first FAci reduced CMT fluctuations and the need for early additional treatments.

Digital Health Multilingual Ontology to Index Teaching Resources.

The aim of this paper is to present the use of Medical Informatics Multilingual Ontology (MIMO) to index digital health resources that are (and will be) included in SaNuRN (project to teach digital health). MIMO currently contains 1,379 concepts and is integrated into HeTOP, which is a cross-lingual multiterminogy server. Existing teaching resources have been reindexed with MIMO concepts and integrated into a dedicated website. A total of 345 resources have been indexed with MIMO concepts and are freely available at https://doccismef.chu-rouen.fr/dc/#env=sanurn. The development of a multilingual MIMO for enhancing the quality and the efficiency of international projects is challenging. A specific semantic search engine has been deployed to give access to digital health teaching resources.

Design and Implementation of a Unique Patient Identification Model in Information Systems in Burkina Faso.

The implementation of a reliable identity process is the basis of any secure patient information sharing system. Indeed, each individual is unique and should be identified by a unique number (identifier). It is with these issues in mind that we have designed and implemented a unique patient identification method adapted to the context of Burkina Faso. The recommended method is inspired by the French method based on the work of the Group for the Modernization of the Hospital Information System (GMSIH) [1]. The developed model allows to assign a "Unique Identifier" (PatientID) to each patient from his profile of identification features (name, date of birth, gender,…). The patient ID is a sequence of 20 characters plus a security "key" of 2 characters. A reliability test of the model has been performed to take into account identity anomalies (duplicate, collision).

Design of an Application for the Automatic Assessment of the Quality of Data Produced in an African Context (Burkina Faso) "Package Data Quality Assessment (PackDQA)".

We have developed data quality tool in R language. Our application name is Package-Data-Quality-Assessment (PackDQA)". It developed following five points: Quality dimension approaches identification, design of quality measures, global coefficient design, development of the quality model, test and deployment model. This model test performed on health data in Burkina Faso show 97.69% observations is quality. The current version does not include qualitative data. We will have to improve theme to use all types of data.

Implementation of a Monitoring System for Pregnancy by Tele-Ultrasound in an African Context (Burkina Faso).

Prenatal ultrasound is a radiological examination that allows optimal follow-up of pregnancies. However, its implementation remains limited in poor countries due to a lack of equipment and trained health workers, such as in Burkina Faso. The aim of this work is to set up an ultrasound tele-expertise system. To achieve this objective, we mobilized human, material and IT resources. The design of the tele-expertise application was based on a generic open source software called "MedShakeEHR" that we have adapted to our context. The application runs in a network on a Linux system. It enables ultrasound data exchange and sharing with a remote expert for interpretation using the DICOM protocol. This device thus offers the possibility to pregnant women to carry out their prenatal ultrasound locally. It also allows the constitution of prenatal ultrasound database according security and confidentiality standards.

Mobile Monitoring of Diabetic Patients in the Active File of the Medical Center of Do (Burkina Faso).

The care of diabetic patients in peripheral medical centers in Burkina Faso faces many difficulties. This work, which is a new experience, aimed to set up an information system for the care of diabetic patients in the context of Burkina Faso. The system thus conceived consists of a web application (MedshakeEHR), used by the doctor and a mobile application (Glucosio) for the patient. The system has advantages such as remote appointment scheduling, appointment reminder, patient information sharing. The device also makes it possible to store data for the production of statistics and for scientific research. This experience has enabled us to meet certain challenges related in particular to the problem of HIS such as organizational constraints, the creation of a unique identifier, the modeling of the main business processes, etc.

Design and Implementation of a Computerized Management System for Adverse Drug Reactions at the Sourô SANOU University Hospital (CHUSS) in Bobo-Dioulasso, Burkina Faso.

Pharmacovigilance is the science and activities related to the detection, evaluation, understanding and prevention of adverse drug reactions or any other possible drug-related problems. In our tropics, this discipline is in an embryonic state. The availability of a management system capable of responding to pharmacovigilance activities is the main objective of our study. The coding was done on the DJANGO Framework. Signal detection was done using the ROR method. We designed three modules which are the notification module, the analysis module and the statistics module. This study has allowed us to launch the basis for a computerization of the pharmacovigilance information system and partly meets our objective. However, it could lead to the integration of the dictionary of adverse effects such as MedDRA as well as the International Classification of Medicines (ATC, EphMRA).

Patient's Unique Identifier for Efficient and Secure Monitoring of Pregnant Women in Burkina Faso.

The objective of this work is to set up a device allowing to identify the pregnant woman in a univocal and reliable way during her pregnancy follow-up. This study is a continuation of a project to improve the electronic monitoring of pregnancy in pregnant women in Burkina Faso. The methodology is based on the scientific work of the GMSIH of France (1). The work has lead to the design and implementation of a model that allows to assign a "Unique Identifier" to each pregnant woman from her first prenatal visit. The Patient ID is developed from the person's identification trait profile. It consists of a sequence of 20 characters and a security "key" of 2 characters. After the design, a reliability test of the model was performed to take into account identity anomalies (duplicates, collisions).