Nowadays, trendy research in biomedical sciences juxtaposes the term ‘precision’ to medicine and public health with companion words like big data, data science, and deep learning. Technological advancements permit the collection and merging of large, multi-source, heterogeneous datasets, from genome sequences to social media posts or from electronic health records to wearable techs. Statistical and machine learning, supported by high-performance computing, in principle allow one to transform these large datasets into knowledge. Despite such progress, many barriers still exist against tangible, translational products for the benefit of the individual and the population. This seminar provocatively focuses on the ‘schmucks’ that litter precision medicine and precision public health, further reviewing methodological and operational hurdles related to the development of prediction/intervention models of health risks, diagnoses and outcomes from integrated biomedical databases.
Mattia Prosperi is an Associate Professor (Preeminence) at the University of Florida. His research interests are in the areas of data science and biomedical modelling. He leads his research group towards the development of original algorithms and applications, exploiting machine learning with a critical eye on causality, and designing usable tools. His theoretical research is focused on the development of new computational intelligence approaches tailored to the analysis of high-dimensional and heterogeneous data (e.g. unstructured social and behavioral data, electronic medical records, multi-omics sequencing data). His applied research foresees the development of prediction and intervention (i.e. counterfactual) models of future life statuses, with a focus on precision medicine and public health. Mattia is head of the Data Intelligence Systems Lab (DISL, https://epidemiology.phhp.ufl.edu/people/faculty-staff/faculty/core-faculty/mattia-prosperi/data-intelligence-systems-lab-disl/) at University of Florida, promoting interdisciplinary team science, education, and scholarly activities. He is the organizer of the “International Bioinformatics Workshop on Virus Evolution and Molecular Epidemiology,” and is the editor of “BMC Medical Informatics and Decision Making” and “Global Health Research and Policy.” He is also the member of the Association for Computing Machinery (ACM), the American Medical Informatics Association (AMIA), and program member of several international conferences, including ACM’s Conference on Bioinformatics, Computational Biology, and Health Informatics.
