An AI powered tool to identify and assess fit-for use registries for real-world evidence
Event: EuroDURG 2025, Uppsala, Sweden Authors: Ghinwa Y. Hayek, Pascal Godbillot, Coriande Clemente, Sonia Zebachi, Gaëtan Pinon, Boris Kopin, Elisabeth Bakker, Sieta T. de Vries, Peter G.M. Mol, Billy Amzal View publication Abstract The selection of appropriate real-world data (RWD) sources, particularly registries, is of primary concern for academia, industry, regulators, and health technology assessment […]
Machine learning achieves promising performance in early diagnosis of rare diseases
Delays in the diagnosis of rare genetic conditions such as acid sphingomyelinase deficiency (ASMD) highlight the necessity for diagnostic algorithms to help clinicians identify patients at high risk of such diseases. To address this, electronic health records (EHRs) and machine learning (ML) were used to develop an ASMD diagnostic algorithm, which achieved promising results. In […]
Tailored diagnostic decision tree resulting from machine learning to improve early diagnosis of ASMD
Event: WORLDSymposium 2024 San Diego, USA Authors: M. Domenica Cappellini, R. Giugliani, M. Törnqvist, P. Guilmin, C.Clémente, M. Montmerle, A. Chiorean, T. Reppelin, Stefaan Sansen, Alexandra Dumitriu, Neha Shah, Maja Gasparic View Poster Abstract Acid sphingomyelinase deficiency (ASMD) is a rare and debilitating lysosomal storage disease and delays in diagnosis are common. We employed machine learning (ML) on electronic health […]
A machine learning algorithm to identify persons at risk of Gaucher disease using EHR in the United States
Gaucher disease is a rare inherited lysosomal storage disorder (LSD) which mainly leads to hepatosplenomegaly, anemia, thrombocytopenia, bone lesions/symptoms, and neurological impairment. Its progressive clinical manifestations are often highly debilitating, shorten lifespans and are considerably variable.
Machine learned decision tree for diagnosis of ASMD among patients with unexplained Interstitial Lung Disease
Event: European Respiratory Society (ERS) International Congress 2023, Milan, Italy Authors: I. Noth, F. Bonella, W.A. Wuyts,P. Guilmin, M. Törnqvist, S. Sansen, A. Dumitriu, N. Shah, M. Gasparic, M. Montmerle View Poster Background Patients with acid sphingomyelinase deficiency (ASMD), a rare lysosomal storage disease, suffer interstitial lung disease (ILD) as a common clinical manifestation. Patients […]
Development of a rare disease algorithm to identify persons at risk of Gaucher disease using Electronic Health Records (EHR) in the United States
Publisher: Orphanet Journal of Rare DiseasesAuthors: A. Wilson, A. Chiorean, M. Aguiar, D. Sekulic, P. Pavlick, N. Shah, L. Sniderman King, M. Génin, M. Rollot, M. Blanchon, S. Gosset, M. Montmerle, C. Molony, A. Dumitriu View publication Background Early diagnosis of Gaucher disease (GD) allows for disease-specific treatment before significant symptoms arise, preventing/delaying onset of complications. Yet, […]
L’intelligence artificielle au service de la modélisation de maladies en vie réelle : vision, exemples et impact sur l’évaluation des médicaments
Event: Colloque de Données de Santé en vie réelle, AFCROs 2023, Boulogne-Billancourt, France Authors: M. Génin, M. Rollot, A. Movschin, B. Amzal, J. Tanniou View Poster Introduction Le rôle des données de vie réelle (RWD) devient de plus en plus important dans les évaluations réglementaires et HTA, en compléments des essais randomisés (RCT), notamment pour anticiper […]
AI/ML in Precision Medicine: A Look Beyond the Hype
Publisher: Therapeutic Innovation & Regulatory Science (Springer Nature Link)Authors: Z. Xu, B. Biswas, L. Li, B. Amzal View publication Background Artificial Intelligence (AI) and Machine Learning (ML) are making headlines in medical research, especially in drug discovery, digital imaging, disease diagnostics, genetic testing, and optimal care pathway (personalized care). Patients and methods However, the potential uses and […]
Machine Learning (ML) applied to real-world data to guide prescription of immune-therapies in metastatic melanoma: a pilot study
Event: ISPOR Global 2023, Boston, MA, USA Authors: F. Gwadry-Sridhar, Billy Amzal View Poster Objectives: Newly diagnosed metastatic melanoma patients are often treated with molecular targeted therapy (TT) or with immunotherapy (IO). However, only a limited proportion of patients respond to those therapies, resulting in reduced survival and substantial inefficiencies for health systems. The purpose […]
Estimating the pertussis burden in adolescents and adults in the United States between 2007 and 2019
Publisher: Taylor & Francis OnlineAuthors: D. Macina, S. Mathur, M. Dvaretskaya, S. Ekhtiari, P. Hayat, M. Montmerle, C.Daluwatte View publication Objectives We developed a machine learning algorithm to identify undiagnosed pertussis episodes in adolescent and adult patients with reported acute respiratory disease (ARD) using clinician notes in an electronic healthcare record (EHR) database. Here, we utilized the algorithm to […]
