Ethicara for Responsible AI in Healthcare: A System for Bias Detection and AI Risk Management.

The increasing torrents of health AI innovations hold promise for facilitating the delivery of patient-centered care. Yet the enablement and adoption of AI innovations in the healthcare and life science industries can be challenging with the rising concerns of AI risks and the potential harms to health equity. This paper describes Ethicara, a system that enables health AI risk assessment for responsible AI model development.

EstimATTR: A Simplified, Machine-Learning-Based Tool to Predict the Risk of Wild-Type Transthyretin Amyloid Cardiomyopathy.

Background: Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM), an increasingly recognized cause of heart failure (HF), often remains undiagnosed until later stages of the disease.

Methods And Results: A previously developed machine learning algorithm was simplified to create a random forest model based on 11 selected phenotypes predictive of ATTRwt-CM to estimate ATTRwt-CM risk in hypothetical patient scenarios. Using U.