Artificial Intelligence Applications in Healthcare and Biomedicine

Organizers and Chairs:

• Abdulhamit Subasi, Faculty of Medicine, University of Turku, Turku, Finland

Date: Monday, 12.06.2023
Time: 15:30 - 17:30
Room: Holiday

Abstract

Artificial Intelligence (AI) applications have emerged as game-changers in healthcare and biomedicine, transforming the landscape of medical research and patient care. AI algorithms have the ability to process and analyze massive amounts of data, enabling faster and more accurate diagnosis of diseases. By leveraging machine learning techniques, AI can identify patterns and anomalies in medical images, such as X-rays and mammograms, facilitating early detection of conditions like tumors and abnormalities. This not only improves patient outcomes but also reduces the burden on healthcare systems by enabling early intervention and preventive measures.
In addition to diagnosis, AI has also proven its potential in personalized medicine and treatment planning. By analyzing patient data, including genetic profiles and medical histories, AI algorithms can generate tailored treatment plans that take into account individual factors such as genetic predispositions, lifestyle choices, and drug interactions. This personalized approach allows healthcare professionals to optimize treatment strategies, improving efficacy and reducing the risk of adverse effects. Furthermore, AI-powered virtual assistants and chatbots are enhancing patient engagement and support by providing 24/7 access to accurate medical information, answering queries, and even monitoring patient health remotely. As AI continues to advance, its applications in healthcare and biomedicine hold great promise for improving patient outcomes, increasing efficiency, and driving innovation in the field.

Organizers Biography

Abdulhamit Subasi is specialized in Artificial Intelligence, Machine Learning, Biomedical Signal and Image Analysis. Concerning application of machine learning to different fields, he wrote more than 30 book chapters and more than 200 published journal and conference papers. He is also author of the books, “Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques”, “Practical Machine Learning for Data Analysis Using Python” and “Applications of Artificial Intelligence in Medical Imaging”. He worked at many institutions as an academician and Georgia Institute of Technology, Georgia, USA, as a researcher. He has been awarded with the Queen Effat Award for Excellence in Research, May 2018. He worked as a professor of computer science at Effat University, Jeddah, Saudi Arabia between 2015 and 2020. Since 2020, he has been working as a Professor at Faculty of Medicine, University of Turku, Turku, Finland.