The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
IEEE

Optimizing Machine Learning-Based Ovarian Cancer Prediction Through Normalization Strategies

Abstract: Ovarian cancer is one of the most challenging cancers to detect early, often leading to poor survival rates. This study explores supervised and unsupervised machine learning and deep ...
GitHub

ImgEdit: A Unified Image Editing Dataset and Benchmark

ImgEdit is a large-scale, high-quality image-editing dataset comprising 1.2 million carefully curated edit pairs, which contain both novel and complex single-turn edits, as well as challenging ...
IEEE

Comparative Study of Machine Learning and Deep Learning Models for Early Prediction of Ovarian Cancer

Abstract: Ovarian cancer remains one of the most difficult gynecological cancers to detect early, often resulting in poor survival rates. This study presents a comparative analysis of machine learning ...