Artificial Intelligence in Healthcare Applications Challenges and Opportunities for Improved Patient Outcomes

¹ Medical Instrumentation Department, Technical Institute of Babylon, Al-furat Al-AWsat Technical University, Babylon, Iraq
² Professor and Head, Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, Telangana, India
³ Assistant Professor, Department of Computer Science and Engineering, CVR College of Engineering, Hyderabad, Telangana, India
⁴ Assistant Professor, Department of Mathematics, SRM TRP Engineering College, Irungalur, Tiruchirapalli, Tamil Nadu, India
⁵ Assistant Professor, Department of Computer Science and Engineering, Bharati Vidyapeeth’s College of Engineering, A-4, Rohtak Road, Paschim Vihar, Delhi, India
⁶ Professor, Department of Mechanical, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India

Zahraa.mrashid@atu.edu.iq
drbalaramallam@gmail.com
lavanya.chintamalla89@gmail.com
shyamkarthi12@gmail.com
mohit.t.bvcoe@gmail.com
chidambaram.pk@newprinceshribhavani.com

Abstract

AI has the potential to revolutionize healthcare by enabling more accurate diagnoses, more effective treatment regimens, and improved patient outcomes. While AI is promising, many challenges remain including limited case studies from the real world, regulatory pressure, bias in data and integration into existing health care delivery systems. In this research we intend to overcome these challenges by designing a comprehensive framework to enhance transactive adoption of AI in healthcare. Cohorts combined with longitudinal case studies advance the study; ethical perspectives, data quality improvement, and bias mitigation emphasises justification for the validity and generalizability of the AI technologies used, which improves the quality of the study. Focus of the Research The research attempts to build interoperable AI systems (which can connect with current healthcare infrastrukture) by Ideating solutions for scalable AI Integration Additionally, it also discusses the challenges posed by hackers and criminal organisations, along with measures to promote patient data privacy, regulatory compliance, and the long-term effects of artificial intelligence on patient healthcare. Such understanding may facilitate an adequate implementation of AI by healthcare professionals and organizations as to impact patient safety, decrease costs and increase the outcome of patient population sorting for different clinical environments.