Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling
The emphasis on fairness in predictive healthcare modeling has increased in popularity as
an approach for overcoming biases in automated decision-making systems. The aim is to …
an approach for overcoming biases in automated decision-making systems. The aim is to …
Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis
Background Robust predictive models of clinical impairment and worsening in multiple
sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies …
sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies …
[HTML][HTML] Enhancing fairness in disease prediction by optimizing multiple domain adversarial networks
Predictive models in biomedicine need to ensure equitable and reliable outcomes for the
populations they are applied to. Unfortunately, biases in medical predictions can lead to …
populations they are applied to. Unfortunately, biases in medical predictions can lead to …
ADC-RBK: a multimodal approach for early detection of chronic diseases and focusing on Alzheimer's
D Shiny Irene, M Lakshmi, LR Kumar… - Progress in Artificial …, 2024 - Springer
Chronic diseases are the most deadly and complex diseases to be treated across the world.
It affects the daily activities of the patients and makes them bedridden. Millions of individuals …
It affects the daily activities of the patients and makes them bedridden. Millions of individuals …