9th International Conference on ICT for Sustainable Development

Authors - Akash Kumar Sinha, Geddam Varahagiri, K. Suresh Babu, Vikram Neerugatti, Santhosh Boddupalli, J Somasekar
Abstract - Machine learning algorithms are essential for deriving actionable insights and forecasts from large datasets in the big data era. This study explores the field of machine learning by examining how various algorithms are applied and performed on a particular dataset. The goal is to determine which machine learning algorithms produce the most accurate and dependable results by comparing how well they handle the complexities of the provided dataset. Heart disease is a major cause of morbidity and death as well as a major global health concern. Preventive healthcare relies heavily on the early identification and precise prediction of heart diseases. In the field of medicine, machine learning techniques have proven to be effective tools for diagnosing and predicting a wide range of illnesses, including heart diseases. This study explores Heart Diseases through the application of Artificial Intelligence and Machine Learning (AIML) techniques, with a particular emphasis on a large dataset that offers priceless insights into this important subject.