A5041184184- Multiple Sclerosis Research Studies
- Ginkgo biloba and Cashew Applications
- Artificial Intelligence in Healthcare and Education
- Bioinformatics and Genomic Networks
- Speech and dialogue systems
- Explainable Artificial Intelligence (XAI)
- Clinical practice guidelines implementation
- Healthcare Systems and Practices
- Cell Image Analysis Techniques
- Health, Medicine and Society
- Biomedical Text Mining and Ontologies
- Gene expression and cancer classification
- Electronic Health Records Systems
- Cytokine Signaling Pathways and Interactions
- Advanced Biosensing Techniques and Applications
- AI in cancer detection
- Machine Learning in Healthcare
- Systemic Lupus Erythematosus Research
- RNA and protein synthesis mechanisms
- Intelligent Tutoring Systems and Adaptive Learning
- Business Strategy and Innovation
Laboratoire des Sciences du Numérique de Nantes
2021-2024
IMT Atlantique
2022-2024
Nantes Université
2022-2024
Inserm
2022-2024
Centre National de la Recherche Scientifique
2022-2024
École Centrale de Nantes
2022
Center for Research in Transplantation and Translational Immunology
2022
Institut de Transplantation Urologie en Nephrologie
2022
Laboratoire d'Automatique, Génie Informatique et Signal
2021
Machine learning (ML) models have proven their potential in acquiring and analyzing large amounts of data to help solve real-world, complex problems. Their use healthcare is expected physicians make diagnoses, prognoses, treatment decisions, disease outcome predictions. However, ML solutions are not currently deployed most systems. One the main reasons for this provenance, transparency, clinical utility training data. Physicians reject if they at least based on accurate do clearly include...
Abstract Background and purpose Multiple sclerosis (MS) is a complex autoimmune disease of the central nervous system, with numerous therapeutic options, but lack biomarkers to support mechanistic approach precision medicine. A computational medicine could proceed from clinical decision systems (CDSSs). They are digital tools aiming empower physicians through applications information technology massive data. However, process their development still maturing; we aimed review it in field MS....
Abstract Objective Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective to use on‐demand computational power address the challenges of dynamically managing MS. Methods A phase 3 clinical trial data (NCT00906399) were used contextualize medication efficacy peg‐interferon beta‐1a vs placebo on patients relapsing–remitting MS (RRMS). Using set reference (PORs), selected based adequate features similar those an individual patient, we...
In personalized medicine, care individualization is a key challenge to provide more adapted and clinical decision for each patient. The access large amounts of medical data with the available computational power as well evolution Artificial Intelligence (AI) algorithms allow overcome this challenge. However, application AI must enable efficient accurate communication physicians. complementarity between human artificial intelligence holds most promise safe innovative future. We propose new...
The knowledge of processes related to protein activation is directly a cascade genes and inhibition. study gene expression allows select differentially expressed potentially involved in similar process. However, some with common biological characteristics are not selected terms expression. use ontology which reliable source information on could conduct improve the selection