A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

aDepartment of Radiodiagnosis, Postgraduate Institute of Medical Education and Research, Chandigarh, 160012, India bDepartment of Clinical Hematology and Medical Oncology, Postgraduate Institute of ...

The ADORE dataset serves as a benchmark to explore the potential and limitations of machine learning in ecotoxicology. It focuses on acute mortality in fish, crustaceans, and algae. It has been ...

Abstract: Skin cancer is well known medical issue and early detection dramatically improves the outcome of treatment. Traditional diagnosis depends on dermatologists ...

Scientists in South Korea have made a breakthrough in colorectal cancer research, the second-most common cause of cancer casualties in the United States. The illness refers to an abnormal growth of ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

The Comprehensive Lung Cancer Imaging Dataset (CLID) is a curated collection of medical images designed to facilitate the research and development of machine learning models for lung cancer analysis.