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Article

Prediction of Parkinson's disease pathogenic variants using hybrid Machine learning systems and radiomic features.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) - 1 Sept 2023

Hajianfar Ghasem, Kalayinia Samira, Hosseinzadeh Mahdi, Samanian Sara, Maleki Majid, Sossi Vesna, Rahmim Arman, Salmanpour Mohammad R

Abstract excerpt

PURPOSE: In Parkinson's disease (PD), 5-10% of cases are of genetic origin with mutations identified in several genes such as leucine-rich repeat kinase 2 (LRRK2) and glucocerebrosidase (GBA). We aim to predict these two gene mutations using hybrid machine learning systems (HMLS), via imaging and non-imaging data, with the long-term goal to predict conversion to active disease. METHODS: We studied 264 and 129...

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Source

Identifiers

PMID: 37579523
DOI: 10.1016/j.ejmp.2023.102647

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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