Freelancer profile translated to English.
Back to original languageAbout Gladis
◉ A little about me ⤵︎
👨💻 I am an expert in **Medical Imaging**, Computer Vision, and Deep Learning
🎓 Certified in AI and data analysis
⚙️ 95% sensitivity and 94% specificity on an AI prototype validated in a University Hospital Center
🧑💼 +9 years of experience in Healthcare
Contribution in 7 structures
I transformed raw MRIs into clinical modules used in surgery
I wrote QA protocols to securemulticenter clinical trials
I went from the MRI table to AI modeling… without ever leaving the medical world
◉ My references ⤵︎
Nurea, Avicenna.Ai, Banook Imaging, ICM - Montpellier Cancer Institute
◉ Here are the missions I regularly undertake ⤵︎
Data Scientist | Health AI | Medical Visualization
Translation of complex medical results into visualsunderstandableby practitioners
Creation of medical decision support modules integrated into clinical workflows
Data set preparation: extraction, normalization, documentation
Training and validation of predictive models in conjunction with R&D or medical teams
Design of dashboards for clinical research or patient monitoring
Structuring databases to facilitate multi-criteria analysis or treatment personalization
Transmission of results in a usable format for doctors, patients, and partners
Quality Control | Dataset Normalization | Clinical Research Support
Manual segmentation of medical images for the creation of AI datasets
Structuring image processing pipelines: DICOM, anonymization, annotation, documentation
Support for clinical teams in interpreting and exploiting results
Contribution to the traceability and reproducibility of multicenter studies
Support for doctoral students and medical researchers on exploratory and statistical analysis
Available 7 days a week via Malt messaging.
Response within one hour.
French
Native or bilingual
English
Conversational
Spanish
Basic
Remote only
Primarily works remotely
Experience
- Institut du Cancer MontpelliérainPermanent Data ScientistHEALTH AND WELLNESSSeptember 2023 - Today (2 years and 11 months)Montpellier, FranceThe Montpellier Cancer Institute wanted to structure and exploit large volumes of clinical data, which are too often underutilized.Medical teams lack visualization and analysis tools to support their decisions, especially in critical contexts such as rectal cancer surgery.The project is still in the prototyping phase. The initial tests aim to evaluate the impact on medical time and the fluidity of the patient pathway.Actions taken:- Structuring databases, normalizing workflows, documenting research data- Supporting doctoral students in the analysis and interpretation of data from clinical studies- Designing an interactive dashboard to make study results immediately usable by researchers- Developing a decision support module for surgeons, aiming to automatically generate key measurements from MRIs- Integrating tumor detection and segmentation components to reduce the time between diagnosis and surgical planning
- Institut du Cancer MontpelliérainFixed-term Research EngineerHEALTH AND WELLNESSMarch 2023 - August 2023 (5 months)Montpellier, FranceThe ICM is conducting a research project on pancreatic cancer, where clinical signs often appear at an advanced stage.With the arrival of a new MRI-guided radiotherapy technology, the need was to anticipate recurrence risks and adapt therapeutic protocols.I was asked to contribute to a doctor's thesis, focused on developing prognostic models.Actions taken:- Extraction of clinical and radiomic data from medical imaging (conversion into usable tabular formats)- Creation of a multiparametric dataset from a cohort of treated patients- Statistical analysis to identify early markers of survival and recurrence- Regular transmission of results to the research doctor to feed into the modeling- Independent work on the entire pipeline, from raw data to analysis👉 Results obtained:- Initial results allowing patients to be stratified according to their risk level (low or high), paving the way for personalized therapeutic decisions- The project is still ongoing, as part of the thesis titled "Development of multiparametric prognostic models in MRI-guided stereotactic radiotherapy for pancreatic cancers"
- Nurea SoftResearch Engineer InternshipHEALTH AND WELLNESSApril 2022 - September 2022 (5 months)Bordeaux, FranceNurea develops medical imaging solutions to secure the post-operative monitoring of patients with aortic aneurysms.The team needed a reliable model to assist doctors in detecting endoleaks on CT scans, a complication that can lead to aortic rupture.I was involved in building a training dataset to enable the automation of this critical detection.Actions taken:- Creation of a usable dataset from manually segmented medical images- Training and evaluation of an endoleak detection model, with regular performance reviews by the CEO (medical profile)- Continuous improvement of the model through an error analysis loop and consideration of edge cases- Definition of relevant decision criteria for use in supporting medical diagnosis- Visualization of results to facilitate interpretation by hospital teams👉 Results obtained:- Prototype validated with 95% sensitivity and 94% specificity- Improvement in post-operative monitoring, with a tool now integrated into Nurea's offering and used in the University Hospitals of Bordeaux and Lyon- Initial positive feedback from user physicians, confirming the relevance of the approach
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Education
- Machine Learning EngineerData Scientist2023En partenariat avec les MINES PariTech | PSL Executive Education RNCP niveau 7 (Bac +5) - 36129 « Chef de projet en intelligence artificielle » Projet fil rouge : Kidney Tumor Segmentation 2021 Segmentation automatique des reins, des tumeurs et des kystes sur des imageries médicales (scanner) Compétences acquises sur le parcours Data Scientist : Machine Learning Supervisé, Non Supervisé et Avancé ; Big Data et Data Base ; Deep Learning ; Système complexe et IA Compétences acquises sur le parcours MLOps : Programmation avancée (Bash, Git, Tests Unitaires) ; DataOps - Isolation (FastAPI, sécurisation des API, Docker, Bootstraps) ; DataOps - Orchestration (Kubernetes, Airflow) ; ModelOps (MLFlow et acculturation Data).
- Data AnalystOpen Classrooms2022En partenariat avec l’ENSAE-ENSAI Titre RNCP niveau 6 - 34964 Compétences acquises : Analyse exploratoire des données, Data Visualisation, Requêtes SQL, Tests statistiques, Réduction de dimension (ACP), Clustering (KMeans), Classification (Régression Logistique), Séries Temporelles.
Certifications
- Machine Learning EngineeringData Scientist2023