Predictors of Splenectomy Response in Immune Thrombocytopenia: A Multicentric Italian Study.

: Splenectomy leads to a high rate of remission in chronic primary immune thrombocytopenia (ITP), but its unpredictable long-term positive outcomes and that it is a irreversible surgical approach discourage clinicians and patients. The identification of predictors of response may redefine the timing of splenectomy. In this retrospective, multicentric study we aimed to investigate clinical-histological predictors of splenectomy response in ITP patients and provide an easy-to-use score to predict splenectomy response in ITP.

Explainable machine learning on clinical features to predict and differentiate Alzheimer's progression by sex: Toward a clinician-tailored web interface.

Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasive, lacking consideration of sex-based differences. This study introduces an explainable machine learning (ML) system to predict and differentiate the progression of AD based on sex, using non-invasive, easily collectible predictors such as neuropsychological test scores and sociodemographic data, enabling its application in every day clinical settings.