Clustering Health Care Data
Speaker:
Prof. Pasi Fränti
School of Computing
University of Eastern Finland
Abstract:
Clustering can be a powerful tool in analyzing healthcare data. We show how clustering algorithms can be used to extract new insight from various health data with the aim to better optimize the future health care system. We first show that simple variants of k-means and random swap algorithms can provide highly accurate clustering results. We demonstrate how k means can be applied to categorical data, sets, and graphs. We model health care records of individual patients as a set of diagnoses.
We apply the methods to cluster both patients and diseases by creating co-occurrence graph of diagnoses depending how often the same pair of diseases is diagnosed in the record of the same patient. Utilizing the order of the appearance, we can construct a predictor for likely future diseases based on the patients past health record. We also cluster locations of health care systems based on patient locations. As a case study, we consider coronary heart disease patients and analyze in what way the optimization of the locations can affect the expected time to reach the hospital within given time.
All the results can provide additional statistical information to health care planners, and medical doctors at the operational level to guide their efforts to provide better health care services.
Biography:
Pasi Fränti received his MSc and PhD degrees from the University of Turku, 1991 and 1994 in Computer Science. Since 2000, he has been a professor of Computer Science at the University of Eastern Finland. He has published over 116 journals and 179 peer review conference papers. Pasi Fränti is the head of the Machine Learning research group. His research interests include clustering algorithms, location-based services, machine learning, web and text mining, and optimization of health care services. He has supervised 31 PhD graduates and is supervising eight more in the areas of clustering (10), location-based services (5), image and audio compression (5), speech technology (4), image processing including segmentation, denoising and HDR (4), web and social media analysis (2), AI in healthcare (2), robotics (1), music composition (1), smart grid (1).
Pasi Fränti’s free time hobbies include sport activities including running, orienteering, football, floorball, ice swimming, chess and marathons. He has completed 50 marathons including twice in Hong Kong (2009 and 2020). He is also the inventor of running chess, football chess and other multisport.
Enquiries: Mr Jeff Liu at Tel. 3943 0624