Mehdi Felfli

Applied machine learning, multi-omics, and statistical modeling to predict patient response, disease progression, survival, and patient selection in imaging clinical trials. Provided methodological and statistical expertise for imaging clinical trial design, endpoint selection, and biomarker validation.

Drafted research protocols, including data selection, sample size determination, and power analysis for clinical studies. Developed AI validation methodologies for clinical study design, data processing, statistical analysis, and performance metrics.

Studied lymphocyte activation and EBV susceptibility in immunodeficient patients presenting a lymphoproliferative disorder. Utilized molecular biology techniques, cell culture, sequencing, cloning, PCR, cytometry, labelling, and phenotyping.

Provided diagnostic consultations and drug prescriptions across various medical specialties including Gynecology/Obstetrics, Pediatrics, Anesthesia, and Functional Rehabilitation. Performed on-call duties to ensure continuous patient care and emergency response.

Specialized in Bioinformatics with a focus on platform engineering in biology. Gained expertise in medical imaging, surrogate clinical endpoints, and patient response prediction in clinical trials.

Completed a comprehensive medical curriculum, earning the Doctor of Medicine degree. This foundational education provided a strong understanding of clinical practices and patient care.