Revolutionizing Breast Cancer Care: AI-Enhanced Diagnosis and Patient History.

Breast cancer poses a significant global health challenge, demanding enhanced diagnostic accuracy and streamlined medical history documentation. This study presents a holistic approach that harnesses the power of artificial intelligence (AI) and machine learning (ML) to address these pressing needs. This study presents a comprehensive methodology for breast cancer diagnosis and medical history generation, integrating data collection, feature extraction, machine learning, and AI-driven history-taking.

An effective assessment of cluster tendency through sampling based multi-viewpoints visual method.

Social networks are the rich sources to people for sharing the knowledge on health-related issues. Nowadays, Twitter is one of the great significant social platforms to the people for a discussion on topics. Analyzing the clusters for the tweets concerning terms is a complex process due to the sparsity problem.