Sarcouncil Journal of Engineering and Computer Sciences

Abstract: Artificial intelligence is a revolutionary force in modern healthcare provision, artificially modifying medical individual processes through superior computational power and machine learning algorithms. The application of AI technology in healthcare systems is unprecedented across diverse clinical specialties, such as medical image analysis, predictive analytics for anticipating critical events, and clinical decision-making systems that aggregate extensive medical knowledge. Medical imaging procedures exhibit remarkable performance in radiological interpretation, oncological applications, and ophthalmic individual procedures, where deep learning models achieve diagnostic accuracy comparable to expert medical interpreters. Predictive analytics systems enable visionary patient surveillance through real-time risk evaluation, detecting worsening clinical conditions before characteristic manifestations become apparent. This is especially valuable in sepsis prevention and cardiovascular event prediction. Clinical decision support systems excel in diagnosing rare conditions, optimizing treatments, and enhancing workflow by providing health professionals with advanced tools that reuse vast medical databases and generate evidence-based remedial suggestions. Implementation challenges include data quality control, regulatory compliance, and ethical issues surrounding computerized decision-making in clinical environments. AI technology processes complex medical data streams with unprecedented speed and precision, enabling healthcare providers to deliver more accurate, effective, and evidence-based patient care while maintaining established clinical safety norms and professional responsibilities.