Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis

Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis

Abstract Prognosticating Amyotrophic Lateral Sclerosis (ALS) presents a formidable challenge due to patients exhibiting different onset sites, progression rates, and survival times. In this study, we have developed and evaluated Machine Learning (ML) algorithms that integrate Ensemble and Imbalance...

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Bibliographic Details
Main Authors: Fabiano Papaiz, Mario Emílio Teixeira Dourado, Ricardo Alexsandro de Medeiros Valentim, Rafael Pinto, Antônio Higor Freire de Morais, Joel Perdiz Arrais
Format: Article
Language:English
Published: BMC 2024-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Amyotrophic lateral sclerosis
Prognosis
Machine learning
Health informatics
Online Access:https://doi.org/10.1186/s12911-024-02484-5

Internet

https://doi.org/10.1186/s12911-024-02484-5

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