Early classification of multivariate time series using a hybrid HMM/SVM model. - Mohamed F. Ghalwash; Dusan Ramljak; Zoran Obradovic (BIBM, 2012)

Early classification of multivariate temporal observations by extraction of interpretable shapelets. - Mohamed F. Ghalwash; Zoran Obradovic (BMC Bioinform., 2012)

Extraction of Interpretable Multivariate Patterns for Early Diagnostics. - Mohamed F. Ghalwash; Vladan Radosavljevic; Zoran Obradovic (ICDM, 2013)

Early Diagnosis and Its Benefits in Sepsis Blood Purification Treatment. - Mohamed F. Ghalwash; Vladan Radosavljevic; Zoran Obradovic (ICHI, 2013)

D2P2: database of disordered protein predictions. - Matt E. Oates; Pedro Romero; Takashi Ishida 002; Mohamed F. Ghalwash; Marcin J. Mizianty; Bin Xue; Zsuzsanna Dosztányi; Vladimir N. Uversky; Zoran Obradovic; Lukasz A. Kurgan; A. Keith Dunker; Julian Gough (Nucleic Acids Res., 2013)

Utilizing temporal patterns for estimating uncertainty in interpretable early decision making. - Mohamed F. Ghalwash; Vladan Radosavljevic; Zoran Obradovic (KDD, 2014)

False alarm suppression in early prediction of cardiac arrhythmia. - Shoumik Roychoudhury; Mohamed F. Ghalwash; Zoran Obradovic (BIBE, 2015)

Patient-specific early classification of multivariate observations. - Mohamed F. Ghalwash; Dusan Ramljak; Zoran Obradovic (Int. J. Data Min. Bioinform., 2015)

Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster. - Jesse Glass; Mohamed F. Ghalwash; Milan Vukicevic; Zoran Obradovic (AAAI, 2016)

A fast structured regression for large networks. - Fang Zhou; Mohamed F. Ghalwash; Zoran Obradovic (IEEE BigData, 2016)

Joint Learning of Representation and Structure for Sparse Regression on Graphs. - Chao Han 003; Shanshan Zhang; Mohamed F. Ghalwash; Slobodan Vucetic; Zoran Obradovic (SDM, 2016)

Structured feature selection using coordinate descent optimization. - Mohamed F. Ghalwash; Xi Hang Cao; Ivan Stojkovic; Zoran Obradovic (BMC Bioinform., 2016)

Continuous Conditional Dependency Network for Structured Regression. - Chao Han 003; Mohamed F. Ghalwash; Zoran Obradovic (AAAI, 2017)

Exploiting Electronic Health Records to Mine Drug Effects on Laboratory Test Results. - Mohamed F. Ghalwash; Ying Li; Ping Zhang 016; Jianying Hu (CIKM, 2017)

Cost Sensitive Time-Series Classification. - Shoumik Roychoudhury; Mohamed F. Ghalwash; Zoran Obradovic (ECML/PKDD (2), 2017)

Ranking Based Multitask Learning of Scoring Functions. - Ivan Stojkovic; Mohamed F. Ghalwash; Zoran Obradovic (ECML/PKDD (2), 2017)

Minimum redundancy maximum relevance feature selection approach for temporal gene expression data. - Milos D. Radovic; Mohamed F. Ghalwash; Nenad Filipovic; Zoran Obradovic (BMC Bioinform., 2017)

Estimating Causal Multi-Drug-Drug Interaction for Adverse Drug Reactions. - Sanjoy Dey; Ping Zhang 016; Mohamed F. Ghalwash; Zach Shahn; Daby Sow (AMIA, 2018)

eXITs: An Ensemble Approach for Imputing Missing EHR Data. - James V. Codella; Hillol Sarker; Prithwish Chakraborty; Mohamed F. Ghalwash; Zijun Yao 001; Daby Sow (ICHI, 2019)

Temporal Graph Regression via Structure-Aware Intrinsic Representation Learning. - Chao Han 003; Xi Hang Cao; Marija Stanojevic; Mohamed F. Ghalwash; Zoran Obradovic (SDM, 2019)

Finding Causal Mechanistic Drug-Drug Interactions from Observational Data. - Sanjoy Dey; Ping Zhang 016; Mohamed F. Ghalwash; Chandramouli Maduri; Daby Sow; Zachary Shahn (AMIA, 2020)

Leveraging Longitudinal Autoantibody for Phenotyping of Progression Rates to Type 1 Diabetes. - Mohamed F. Ghalwash; Vibha Anand; Kenney Ng; Jessica L. Dunne; Markus Lundgren; Marian Rewers; Riitta Veijola (AMIA, 2020)

Predicting Type 1 Diabetes Onset using Novel Survival Analysis with Biomarker Ontology. - Ying Li; Bin Liu; Vibha Anand; Markus Lundgren; Kenney Ng; Marian Rewers; Riitta Veijola; Mohamed F. Ghalwash (AMIA, 2020)

A Multi-Task Learning Approach to Personalized Progression Modeling. - Mohamed F. Ghalwash; Daby Sow (ICHI, 2020)

G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes. - Rui Li; Zach Shahn; Jun Li 027; Mingyu Lu; Prithwish Chakraborty; Daby Sow; Mohamed F. Ghalwash; Li-Wei H. Lehman (CoRR, 2020)

ODVICE: An Ontology-Driven Visual Analytic Tool for Interactive Cohort Extraction. - Mohamed F. Ghalwash; Zijun Yao 001; Prithwish Chakraborty; James V. Codella; Daby Sow (CoRR, 2020)

Towards Clinically Relevant Explanations for Type-2 Diabetes Risk Prediction with the Explanation Ontology. - Shruthi Chari; Prithwish Chakraborty; Oshani Seneviratne; Mohamed F. Ghalwash; Daniel M. Gruen; Daby Sow; Deborah L. McGuinness (AMIA, 2021)

Impact of Clinical and Genomic Factors on COVID-19 Disease Severity. - Sanjoy Dey; Aritra Bose; Subrata Saha; Prithwish Chakraborty; Mohamed F. Ghalwash; Filippo Utro; Aldo Guzmán-Sáenz; Kenney Ng; Jianying Hu; Laxmi Parida; Daby Sow (AMIA, 2021)

A Comparative Time-to-Event Analysis Across Health Systems. - Mohamed F. Ghalwash; Prithwish Chakraborty; Akira Koseki; Hiroki Yanagisawa; Toshiya Iwamori; Ray Tokumasu; Masaki Makino; Ryosuke Yanagiya; Atsushi Suzuki; Michiharu Kudo; Daby Sow (AMIA, 2021)

Simulating Screening for Risk of Childhood Diabetes: The Collaborative Open Outcomes tooL (COOL). - Mohamed F. Ghalwash; Eileen Koski; Riitta Veijola; Jorma Toppari; William Hagopian; Marian Rewers; Vibha Anand (AMIA, 2021)

Phenotypical ontology driven framework for multi-task learning. - Mohamed F. Ghalwash; Zijun Yao 001; Prithwish Chakraborty; James V. Codella; Daby Sow (CHIL, 2021)

G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime. - Rui Li; Stephanie M. Hu; Mingyu Lu; Yuria Utsumi; Prithwish Chakraborty; Daby M. Sow; Piyush Madan; Jun Li 027; Mohamed F. Ghalwash; Zach Shahn; Li-Wei H. Lehman (ML4H@NeurIPS, 2021)

Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge. - Prithwish Chakraborty; James V. Codella; Piyush Madan; Ying Li; Hu Huang 004; Yoonyoung Park; Chao Yan 004; Ziqi Zhang 005; Cheng Gao; Steve Nyemba; Xu Min; Sanjib Basak; et al. (CoRR, 2021)

Disease Progression Modeling Workbench 360. - Parthasarathy Suryanarayanan; Prithwish Chakraborty; Piyush Madan; Kibichii Bore; William Ogallo; Rachita Chandra; Mohamed F. Ghalwash; Italo Buleje; Sekou L. Remy; Shilpa Mahatma; Pablo Meyer 001; Jianying Hu (CoRR, 2021)

Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case. - Shruthi Chari; Prithwish Chakraborty; Mohamed F. Ghalwash; Oshani Seneviratne; Elif K. Eyigöz; Daniel M. Gruen; Fernando J. Suarez Saiz; Ching-Hua Chen; Pablo Meyer Rojas; Deborah L. McGuinness (CoRR, 2021)

An Ontology for Fairness Metrics. - Jade S. Franklin; Karan Bhanot; Mohamed F. Ghalwash; Kristin P. Bennett; Jamie P. McCusker; Deborah L. McGuinness (AIES, 2022)

Human-centered explainability for life sciences, healthcare, and medical informatics. - Sanjoy Dey; Prithwish Chakraborty; Bum Chul Kwon; Amit Dhurandhar; Mohamed F. Ghalwash; Fernando J. Suarez Saiz; Kenney Ng; Daby Sow; Kush R. Varshney; Pablo Meyer 001 (Patterns, 2022)

Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes. - Shruthi Chari; Prasant Acharya; Daniel M. Gruen; Olivia Zhang; Elif K. Eyigöz; Mohamed F. Ghalwash; Oshani Seneviratne; Fernando J. Suarez Saiz; Pablo Meyer 001; Prithwish Chakraborty; Deborah L. McGuinness (Artif. Intell. Medicine, 2023)

Explanation Ontology: A general-purpose, semantic representation for supporting user-centered explanations. - Shruthi Chari; Oshani Seneviratne; Mohamed F. Ghalwash; Sola Shirai; Daniel M. Gruen; Pablo Meyer 001; Prithwish Chakraborty; Deborah L. McGuinness (Semantic Web, 2024)