- Specialized in semantic segmentation of lung compartments.- Provided precise annotations to facilitate the development of mathematical models for medical imaging analysis.- Trained radiologists in organ segmentation techniques.

Advanced Segmentation of Bronchopulmonary Segments Using Deep LearningObjective: Developed a deep learning model for precise segmentation of the 20 bronchopulmonary segments from CT scans, aimed at improving lung cancer diagnosis and surgical planning.Responsibilities:- Created a comprehensive dataset using Slicer 3D, including manual segmentation of 100 patient scans.- Designed and implemented a U-Net-based model, optimized for 2D and 3D CT scans.- Coordinated data acquisition and annotation, including validation by expert radiologists.- Conducted comparative performance analysis of 2D vs. 3D models using metrics like Dice coefficient and IoU.- Authored the final report highlighting the project’s advancements and clinical implications.Results: Achieved superior performance with the 3D nnU-Net model (Dice: ~0.83, IoU: ~0.72), significantly improving volumetric segmentation accuracy with potential clinical impact.Skills Gained: Medical image segmentation, project management, model performance evaluation, data annotation, scientific reporting.

1. Development and Validation of the 3PDQ for Diagnosing Primary Pain in Parkinson’s DiseaseObjective: Developed and validated a self-assessment questionnaire (3PDQ) to diagnose primary pain in Parkinson’s patients, addressing a critical gap in symptom recognition and treatment.Responsibilities:- Coordinated statistical analysis to validate the 3PDQ’s structure and reliability across 15 Parkinson expert centers in France.- Developed predictive models using machine learning techniques to identify key questionnaire items.- Compared model performance on various metrics (precision, sensitivity, specificity, AUC).- Authored and presented findings, emphasizing potential clinical applications for improved pain management.Results: Reduced the 3PDQ from 28 to 11 items, with moderate predictive performance, suggesting further validation with larger samples.Skills Gained: Questionnaire development, psychometric validation, predictive modeling, research project management, scientific communication.2. Analysis of Sexual Dysfunction in Schizophrenic Patients - Systematic Review and Meta-AnalysisObjective: Conducted a systematic review and meta-analysis to evaluate the prevalence of sexual dysfunction in schizophrenic patients, aiming to inform clinical practices.Responsibilities:- Extracted and analyzed data from 72 studies involving over 21,000 participants across 33 countries.- Applied random-effects models to calculate global and subgroup prevalence rates.- Contributed to manuscript writing, focusing on result analysis and clinical recommendations.Results: Identified high prevalence of sexual dysfunction linked to psychiatric diagnosis severity and psychotropic medication use, highlighting the need for improved screening and treatment strategies.Skills Gained: Systematic review, meta-analysis, advanced statistical analysis, interdisciplinary collaboration, scientific writing.

- Analyzed and manipulated CT and MRI scans.- Conducted 3D liver segmentation using 3D Slicer.

medical intern in cardiac surgery

medical intern in histopathology Dept.