| Federated learning of predictive models from federated electronic health records TS Brisimi, R Chen, T Mela, A Olshevsky, IC Paschalidis, W Shi International journal of medical informatics 112, 59-67, 2018 | 159 | 2018 |
| Prediction of hospitalization due to heart diseases by supervised learning methods W Dai, TS Brisimi, WG Adams, T Mela, V Saligrama, IC Paschalidis International journal of medical informatics 84 (3), 189-197, 2015 | 96 | 2015 |
| Sensing and classifying roadway obstacles in smart cities: The street bump system TS Brisimi, CG Cassandras, C Osgood, IC Paschalidis, Y Zhang IEEE Access 4, 1301-1312, 2016 | 54 | 2016 |
| Predicting chronic disease hospitalizations from electronic health records: an interpretable classification approach TS Brisimi, T Xu, T Wang, W Dai, WG Adams, IC Paschalidis Proceedings of the IEEE 106 (4), 690-707, 2018 | 38 | 2018 |
| Distribution-dependent robust linear optimization with applications to inventory control SC Kang, TS Brisimi, IC Paschalidis Annals of operations research 231 (1), 229-263, 2015 | 16 | 2015 |
| Predicting diabetes-related hospitalizations based on electronic health records TS Brisimi, T Xu, T Wang, W Dai, IC Paschalidis Statistical methods in medical research 28 (12), 3667-3682, 2019 | 15 | 2019 |
| Performance measurement with multiple interrelated variables and threshold target levels: Evidence from retail firms in the US PD Zervopoulos, TS Brisimi, A Emrouznejad, G Cheng European Journal of Operational Research 250 (1), 262-272, 2016 | 13 | 2016 |
| Sensing and classifying roadway obstacles: The street bump anomaly detection and decision support system TS Brisimi, S Ariafar, Y Zhang, CG Cassandras, IC Paschalidis 2015 IEEE International Conference on Automation Science and Engineering …, 2015 | 11 | 2015 |
| A joint sparse clustering and classification approach with applications to hospitalization prediction T Xu, TS Brisimi, T Wang, W Dai, IC Paschalidis 2016 IEEE 55th Conference on Decision and Control (CDC), 4566-4571, 2016 | 8 | 2016 |
| Benefit graph extraction from healthcare policies V Lopez, V Rho, TS Brisimi, F Cucci, M Kristiansen, J Segrave-Daly, ... | 1 | 2019 |
| Automatic generation of logically consistent application code change groups P Tommasi, RHO Valentina, T Brisimi, M Stephenson US Patent App. 16/541,778, 2021 | | 2021 |
| Intelligent learning and application of operational rules VL Garcia, F Cucci, T Brisimi, A Kishimoto, R Marinescu US Patent App. 16/406,856, 2020 | | 2020 |
| Semi-automated correction of policy rules T Brisimi, R Marinescu, A Kishimoto, VL Garcia US Patent App. 16/194,621, 2020 | | 2020 |
| Intelligent recommendation of convenient event opportunities JH Bettencourt-silva, T Brisimi, ML Sbodio, N Mulligan US Patent App. 16/180,699, 2020 | | 2020 |
| EXTRACTING STRUCTURED INFORMATION FROM UNSTRUCTURED DATA USING DOMAIN PROBLEM APPLICATION VALIDATION T Brisimi, S Kotoulas, V Lopez Garcia, V Rho, N Mulligan US Patent App. 16/165,620, 2020 | | 2020 |
| Intelligent learning for explaining anomalies JH Bettencourt-silva, VL Garcia, RHO Valentina, T Brisimi US Patent App. 16/158,030, 2020 | | 2020 |
| Ontology-guided Policy Information Extraction for Healthcare Fraud Detection TS Brisimi, V Lopez, V Rho, M Sbodio, G Picco, M Kristiansen, ... | | 2019 |
| Summary of Best Papers Selected for the 2019 IMIA Yearbook, Section Clinical Research Informatics TS Brisimi, R Chen, T Mela, A Olshevsky, IC Paschalidis, W Shi Int J Med Inform 112, 59-67, 2018 | | 2018 |
| Centralized and distributed learning methods for predictive health analytics TS Brisimi Boston University, 2017 | | 2017 |
Ioannis Ch. PaschalidisProfessor of Electrical and Computer, Systems, and Biomedical Engineering, Boston UniversityVerified email at bu.edu
