| CIBB 2019 Special session on Machine Learning in Healthcare Informatics | |
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Italy - BG - Bergamo |
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| Hosted by: | Davide Chicco (for the special session), Paolo Cazzaniga, Ivan Merelli, Daniela Besozzi (for the CIBB 2019 conference) |
| Venue: | Università di Bergamo |
| Dates: | Sep 04, 2019 through Sep 06, 2019 |
| Call for Proceedings Presentations: | 2019-04-01 through 2019-05-01 |
| Event Registration: | 2019-04-01 through 2019-08-25 |
| Early Registration Deadline: | 2019-07-15 |
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Description |
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| Call for papers This is the call for papers for the special session Machine Learning in Healthcare Informatics and Medical Biology within the 16th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2019) that will be held at Università di Bergamo, Bergamo, Italy, EU. If you are working on a project related to the topics described below, you are warmly invited to submit a short paper to our special session. Aim and scope Machine learning has become a pivotal tool to analyze biomedical and biological datasets, especially in the Big Data era. In fact, machine learning algorithms can identify hidden relationships and structures in health care data, and even take advantage of them to make accurate predictions about similar or future data instances. For example, machine learning software has been able to predict the diagnosis of tumor patients just by processing patients’ clinical features, allowing scientists to save time and money compared to wet lab experiments. Computational researchers have also exploited machine learning to infer knowledge about patients by analyzing biological datasets, especially the ones featuring genetics and epigenomic traits. Data mining approaches applied to such datasets, in fact, can lead to relevant discoveries both to understand molecular biology and to gain new knowledge about patients’ diseases. Our special session on "Machine Learning in Healthcare Informatics and Medical Biology" aims at boosting these scientific fields, calling for researchers able to show the potential and the advance of machine learning algorithms to make accurate computational predictions in health care datasets and in patient-oriented biological datasets. Topics of interest include: Machine learning methods applied to health care and biomedical datasets Machine learning methods applied to genetics and epigenomics datasets, to understand the conditions of healthy and/or sick patients Machine learning methods applied to biological datasets to understand the underlying biomolecular scenario Machine learning software and tools in the health care and biological domain Statistical models to analyze health care, biomedical, and biological datasets Data mining applications in the health care and biological domain |
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| Additional Information | |
| Event URL: | https://davidechicco.github.io/cibb2019specialsession/ |
| ISCB Member Discount: | None |
| Contact Person: | Davide Chicco ([javascript protected email address]) |
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