Sarcouncil Journal of Engineering and Computer Sciences

Abstract: The concept of artificial intelligence has completely changed the nature of healthcare delivery by providing new avenues through which medical practitioners can improve the process of treatment planning and patient care. Combining CI with clinical knowledge is a paradigm shift in the way of diagnosis and the formation of treatment plans. Using advanced data processing and pattern recognition platforms, AI systems analyze huge amounts of patient data to uncover meaningful correlations that may be used to make personalized treatment options. During the clinical consultation session, real-time decision support platforms offer evidence-based suggestions to enhance the accuracy of the diagnostic process and support the effective workflow. Continuous monitoring technologies allow adjusting treatment in advance according to the streams of physiological data from health devices connected, which allows early intervention before the development of complications. Nevertheless, to become successful, the implementation must consider serious ethical implications such as patient privacy, data security, algorithm transparency, and fair access by a wide range of population groups. Medical institutions should develop strong governance systems that can guarantee that AI suggestions supplement instead of substituting human clinical decision-making. Human experience in collaboration with artificial intelligence has enormous potential to enhance patient outcomes with more accurate, personalized, and responsive care delivery and retain the necessary human aspects of compassion and ethical decision-making in medical practice.