Artificial Intelligence in Healthcare: Diagnosis, Treatment, and Prediction Kharibam Jilenkumari Devi 1 , Wajdi Alghamdi 2 , Divya N 3 , Ahmed Alkhayyat 4 , Artikbaeva Sayyora 5 T.Sathish 6 1 Assistant professor, department of ECE, National Institute of Technology Manipur. E-mail: jjkharibam@gmail.com 2 Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Saudi ArabiaE-mail wmalghamdi@kau.edu.sa 3 Assistant Professor, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai – 127 divya.n_civil@psvpec.in 4 College of technical engineering, The Islamic university, Najaf, Iraq. ahmedalkhayyat85@iunajaf.edu.iq 5 Tashkent State Pedagogical University, Tashkent, Uzbekistan 6 Associate Professor,Department of Mechanical Engineering,Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India.sathisht.sse@saveetha.com Abstract- One of the most potential uses of artificial intelligence (AI), which has changed a number of industries, is in healthcare. The application of AI in healthcare is discussed in general in this study, with an emphasis on diagnosis, treatment, and prediction. In the area of diagnostics, AI has proven to be remarkably adept at deciphering X-rays, CT scans, and MRI pictures to spot illnesses and anomalies. A branch of AI known as deep learning algorithms has shown to be particularly good at accurately identifying and categorizing medical disorders. Large volumes of imaging data may be swiftly analyzed by AI systems, enabling medical personnel to diagnose patients more accurately and with fewer mistakes. Additionally, AI may combine patient information, genetic data, and other pertinent data to produce tailored diagnostic suggestions. Consequently, AI has become a game-changing force in healthcare, especially in the disciplines of diagnosis, treatment, and prediction. AI systems can help medical personnel make more precise diagnoses, create individualized treatment plans, and forecast patient outcomes by utilizing machine learning algorithms and advanced data analytics. While there are still difficulties, there are enormous potential advantages for AI in healthcare, and coordinated efforts are required to realize these advantages and assure its ethical and fair incorporation into healthcare systems. I. INTRODUCTION Moving on to healthcare, AI promises important improvements in therapeutic intervention optimization. Large patient data sets, including medical records, treatment results, and clinical recommendations, may be analyzed by machine learning algorithms to create individualized treatment regimens. Based on unique patient features, AI-based decision support systems can help medical professionals choose the best therapies. AI may also continually monitor a patient's physiological data and vital signs, notifying medical staff of any abnormalities or potential issues and improving patient safety and care. Another crucial area of healthcare where AI has demonstrated significant potential is prediction. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/). E3S Web of Conferences 399, 04043 (2023) https://doi.org/10.1051/e3sconf/202339904043 ICONNECT-2023