From Farms to Clinics: Assessing Community Impacts of Machine Learning in Health Care and Technological Advancements in Agriculture

Abstract

This paper explores the intersection of machine learning and technological advancements in agriculture and healthcare, focusing on their community impacts. Machine learning algorithms are transforming agricultural practices by optimizing resource management, enhancing crop yields, and fostering sustainable farming techniques. Concurrently, machine learning is revolutionizing healthcare by enabling early detection and management of chronic conditions such as diabetes, cardiovascular diseases, cancer, and respiratory disorders. By conducting a comparative analysis of these technological advancements, the paper highlights their implications for community well-being, including improved health outcomes, increased food security, and environmental sustainability. The findings aim to provide a comprehensive understanding of how integrating these technologies can drive positive change across sectors and contribute to the overall quality of life in diverse communities.