Thesis Abstract

Abstract
In the era of rapid technological advancements, the healthcare industry is also experiencing a significant transformation. One of the most promising technologies in healthcare is the use of artificial intelligence (AI) and machine learning (ML) algorithms. These technologies have the potential to revolutionize various aspects of healthcare, from diagnostics to personalized treatment plans. This research project aims to explore the applications of AI and ML in healthcare, focusing on their impact on patient care and outcomes. By conducting a thorough review of existing literature and case studies, this study seeks to provide insights into how AI and ML can enhance healthcare delivery and improve patient outcomes. The primary objectives of this research include identifying the key areas within healthcare where AI and ML technologies are being utilized, analyzing the benefits and challenges associated with their implementation, and evaluating the effectiveness of these technologies in improving patient care. Additionally, this study aims to investigate the ethical considerations surrounding the use of AI and ML in healthcare, such as data privacy and algorithm bias. Through a comprehensive analysis of the current landscape of AI and ML applications in healthcare, this research project aims to contribute to the growing body of knowledge in this field. By highlighting the potential benefits and limitations of these technologies, this study seeks to inform healthcare professionals, policymakers, and other stakeholders about the opportunities and challenges associated with integrating AI and ML into clinical practice. Overall, this research project intends to shed light on the transformative potential of AI and ML in healthcare and provide recommendations for harnessing these technologies to improve patient care and outcomes. By understanding the current state of AI and ML applications in healthcare, stakeholders can make informed decisions about adopting these technologies to enhance the quality and efficiency of healthcare delivery.

Thesis Overview