Prediction of quality of life in people with ALS

Author:

Antoniadi Anna Markella1,Galvin Miriam2,Heverin Mark2,Hardiman Orla2,Mooney Catherine1

Affiliation:

1. University College Dublin, Belfield, Dublin, Ireland

2. Trinity College Dublin, Dublin, Ireland

Abstract

Amyotrophic Lateral Sclerosis (ALS) is a rare neurodegenerative disease that causes a rapid decline in motor functions and has a fatal trajectory. ALS is currently incurable, so the aim of the treatment is mostly to alleviate symptoms and improve quality of life (QoL) for the patients. The goal of this study is to develop a Clinical Decision Support System (CDSS) to alert clinicians when a patient is at risk of experiencing low QoL. The source of data was the Irish ALS Registry and interviews with the 90 patients and their primary informal caregiver at three time-points. In this dataset, there were two different scores to measure a person's overall QoL, based on the McGill QoL (MQoL) Questionnaire and we worked towards the prediction of both. We used Extreme Gradient Boosting (XGBoost) for the development of the predictive models, which was compared to a logistic regression baseline model. Additionally, we used Synthetic Minority Over-sampling Technique (SMOTE) to examine if that would increase model performance and SHAP (SHapley Additive explanations) as a technique to provide local and global explanations to the outputs as well as to select the most important features. The total calculated MQoL score was predicted accurately using three features - age at disease onset, ALSFRS-R score for orthopnoea and the caregiver's status pre-caregiving - with a F1-score on the test set equal to 0.81, recall of 0.78, and precision of 0.84. The addition of two extra features (caregiver's age and the ALSFRS-R score for speech) produced similar outcomes (F1-score 0.79, recall 0.70 and precision 0.90).

Publisher

Association for Computing Machinery (ACM)

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1. Unveiling the black box: A systematic review of Explainable Artificial Intelligence in medical image analysis;Computational and Structural Biotechnology Journal;2024-12

2. Amyotrophic Lateral Sclerosis (ALS) Monitoring Using Explainable AI;Studies in Computational Intelligence;2024

3. On Analyzing Complex Data Within Clinical Decision Support Systems;Advances in Medical Technologies and Clinical Practice;2022-11-11

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