SUMMARY
The focus of research for Panagiotis (Panos) Korfiatis, Ph.D., is on integrating artificial intelligence (AI) into healthcare. His research centers on developing and embedding AI algorithms within clinical environments to transform patient care with innovative technology. Dr. Korfiatis' research interests include areas such as:
- Imaging informatics.
- Post-production monitoring.
- Disease detection.
- Multimodal large language models in healthcare applications.
Dr. Korfiatis aims to seamlessly incorporate AI algorithms into clinical workflows. This involves emphasizing the importance of effective monitoring and optimization of these systems in live settings. His research studies also extend to harnessing cutting-edge technologies, such as multimodal large language models, to assist clinicians in their daily workflows.
Focus areas
- Imaging informatics. Dr. Korfiatis studies the integration and monitoring of algorithms within clinical workflows. He also works to enhance the utility and reliability of imaging in diagnostics and patient management.
- AI validation. Dr. Korfiatis studies approaches for validating AI models to ensure their accuracy and reliability in clinical settings. He aims to establish robust standards for AI in healthcare.
- Multimodal large language models. Dr. Korfiatis is working on the development of multimodal approaches that leverage imaging and clinical text. This innovative work aims to create novel applications that improve patient care and outcomes by providing a more holistic view of patient health.
Significance to patient care
Dr. Korfiatis' AI research significantly transforms patient care, making it easier for clinicians to give correct diagnoses, personalize treatments and streamline workflows. His work using imaging informatics and multimodal large language models allows healthcare professionals to find diseases early on and get a more comprehensive understanding of patient health. Emphasizing AI confirmation and effective post-production monitoring makes it certain that these new technologies work dependably and effectively in real-world clinical settings.