چکیده مقاله
The integration of artificial intelligence AI in healthcare has introduced transformative possibilities, particularly through predictive analytics aimed at enhancing patient outcomes This paper explores the application of AI driven predictive analytics in forecasting patient outcomes, focusing on methodologies, benefits, challenges, and future prospects By leveraging large volumes of medical data, AI algorithms can identify patterns and make accurate predictions, improving patient care and optimizing healthcare resources This research delves into various AI techniques, including machine learning and deep learning, and their applications in predicting disease progression, hospital readmissions, and treatment responses It also examines the ethical and regulatory considerations, addressing concerns related to data privacy and algorithmic bias The paper concludes with a discussion on the future directions of AI in healthcare, emphasizing the need for robust validation and seamless integration into clinical workflows The findings highlight the transformative potential of AI driven predictive analytics in enhancing personalized medicine and ultimately contributing to better patient outcomes and healthcare efficiency
کلیدواژهها
نویسندگان
Mahsa Salehi Sichani
University of Science and Research,mahsa salehi cs@gmail com, Isfahan, Iran
شیوه ارجاع
Salehi Sichani, Mahsa,1403,AI-Driven Predictive Analytics for Patient Outcomes,10th International Conference on Interdisciplinary Researches in Electrical, Computer, Mechanical and Mechatronics Engineering in Iran and Islamic World,Tehran
ارائهشده در
مجموعه مقالات دهمین کنفرانس بین المللی تحقیقات بین رشته ای در مهندسی برق، کامپیوتر، مکانیک و مکاترونیک در ایران و جهان اسلام29 شهریور 1403 · تهران