IEEE

A Hybrid Machine Learning Model for Accurate Autism Diagnosis

Abstract: The healthcare industry faces significant challenges in managing and processing large volumes of unstructured, real-time medical data. As such, there is a growing need for advanced ...
IEEE

Quantum Machine Learning: Recent Advances, Challenges, and Perspectives

Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...
Journal of Medical Internet Research

Longitudinal Model Shifts of Machine Learning–Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals

Objective: This study aimed to assess the impact of a model shift on ML-based prediction models by evaluating 3 different use cases—delirium, sepsis, and acute kidney injury (AKI)—from 2 hospitals (M ...
BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...