Journal of Medical Internet Research

Beyond Comparing Machine Learning and Logistic Regression in Clinical Prediction Modelling: Shifting from Model Debate to Data Quality

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...
Morning Overview on MSN

Many AI disease-risk models trained on flawed health data

Somewhere on Kaggle, the open data platform where anyone can upload a spreadsheet and call it a dataset, two files labeled as ...
Tech XploreOpinion

What skills do humans need to become robot proof in the age of AI?

Alumna, author and machine learning expert Vivienne Ming explains why the best defense against AI's downsides is investing in ...
StudyFinds on MSN

AI disease prediction may catch illnesses before symptoms even start

In A Nutshell AI tools that track how the body’s molecular networks change over time may detect diseases like cancer, ...
IEEE

Enhanced Prediction of Diabetes Using Integrated Machine Learning and Deep Learning Techniques

Abstract: Diabetes mellitus is still a considerable public health issue worldwide. Recent advances in machine learning (ML) and deep learning (DL) offer an exciting set of tools to enable early ...
IEEE

Assessing Bias Within Diabetes Risk Prediction in Machine Learning Techniques

Abstract: As machine learning (ML) models increasingly influence clinical decision-making, concerns over fairness and bias have emerged, particularly in predictive healthcare tools. This study ...
Frontiers

External validation and application of a machine learning–based model for diabetes progression in prediabetes

This study externally validated a machine learning–based model for type 2 diabetes progression (ML-PR) and evaluated its clinical utility in individuals with prediabetes. We included 3,081 ...