Mohamed F. Ghalwash

According to our database, Mohamed F. Ghalwash authored at least 39 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

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, Prithwish Chakraborty, Deborah L. McGuinness

Semantic Web, 2024

2023

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, Prithwish Chakraborty, Deborah L. McGuinness

Artif. Intell. Medicine, March, 2023

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

Patterns, 2022

An Ontology for Fairness Metrics.

Jade S. Franklin, Karan Bhanot, Mohamed F. Ghalwash, Kristin P. Bennett, Jamie P. McCusker, Deborah L. McGuinness

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

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

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, Jianying Hu

CoRR, 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, Yoonyoung Park, Chao Yan, Ziqi Zhang, Cheng Gao, Steve Nyemba, Xu Min, Sanjib Basak, Mohamed F. Ghalwash, Zach Shahn, Parthasarathy Suryanarayanan, Italo Buleje, Shannon Harrer, Sarah Miller, Amol Rajmane, Colin Walsh, Jonathan Wanderer, Gigi Y. Yuen-Reed, Kenney Ng, Daby Sow, Bradley A. Malin

CoRR, 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, Mohamed F. Ghalwash, Zach Shahn, Li-Wei H. Lehman

Proceedings of the Machine Learning for Health, 2021

Phenotypical ontology driven framework for multi-task learning.

Mohamed F. Ghalwash, Zijun Yao, Prithwish Chakraborty, James V. Codella, Daby Sow

Proceedings of the ACM CHIL '21: ACM Conference on Health, 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

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 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

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 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

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

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

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

ODVICE: An Ontology-Driven Visual Analytic Tool for Interactive Cohort Extraction.

Mohamed F. Ghalwash, Zijun Yao, Prithwish Chakraborty, James V. Codella, Daby Sow

CoRR, 2020

G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes.

Rui Li, Zach Shahn, Jun Li, Mingyu Lu, Prithwish Chakraborty, Daby Sow, Mohamed F. Ghalwash, Li-Wei H. Lehman

CoRR, 2020

A Multi-Task Learning Approach to Personalized Progression Modeling.

Mohamed F. Ghalwash, Daby Sow

Proceedings of the 8th IEEE International Conference on Healthcare Informatics, 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

Proceedings of the AMIA 2020, 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

Proceedings of the AMIA 2020, 2020

Finding Causal Mechanistic Drug-Drug Interactions from Observational Data.

Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Chandramouli Maduri, Daby Sow, Zachary Shahn

Proceedings of the AMIA 2020, 2020

2019

Temporal Graph Regression via Structure-Aware Intrinsic Representation Learning.

Chao Han, Xi Hang Cao, Marija Stanojevic, Mohamed F. Ghalwash, Zoran Obradovic

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

eXITs: An Ensemble Approach for Imputing Missing EHR Data.

James V. Codella, Hillol Sarker, Prithwish Chakraborty, Mohamed F. Ghalwash, Zijun Yao, Daby Sow

Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019

2018

Estimating Causal Multi-Drug-Drug Interaction for Adverse Drug Reactions.

Sanjoy Dey, Ping Zhang, Mohamed F. Ghalwash, Zach Shahn, Daby Sow

Proceedings of the AMIA 2018, 2018

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

Ranking Based Multitask Learning of Scoring Functions.

Ivan Stojkovic, Mohamed F. Ghalwash, Zoran Obradovic

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Cost Sensitive Time-Series Classification.

Shoumik Roychoudhury, Mohamed F. Ghalwash, Zoran Obradovic

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Exploiting Electronic Health Records to Mine Drug Effects on Laboratory Test Results.

Mohamed F. Ghalwash, Ying Li, Ping Zhang, Jianying Hu

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Continuous Conditional Dependency Network for Structured Regression.

Chao Han, Mohamed F. Ghalwash, Zoran Obradovic

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Structured feature selection using coordinate descent optimization.

Mohamed F. Ghalwash, Xi Hang Cao, Ivan Stojkovic, Zoran Obradovic

BMC Bioinform., 2016

Joint Learning of Representation and Structure for Sparse Regression on Graphs.

Chao Han, Shanshan Zhang, Mohamed F. Ghalwash, Slobodan Vucetic, Zoran Obradovic

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

A fast structured regression for large networks.

Fang Zhou, Mohamed F. Ghalwash, Zoran Obradovic

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster.

Jesse Glass, Mohamed F. Ghalwash, Milan Vukicevic, Zoran Obradovic

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Patient-specific early classification of multivariate observations.

Mohamed F. Ghalwash, Dusan Ramljak, Zoran Obradovic

Int. J. Data Min. Bioinform., 2015

False alarm suppression in early prediction of cardiac arrhythmia.

Shoumik Roychoudhury, Mohamed F. Ghalwash, Zoran Obradovic

Proceedings of the 15th IEEE International Conference on Bioinformatics and Bioengineering, 2015

2014

Utilizing temporal patterns for estimating uncertainty in interpretable early decision making.

Mohamed F. Ghalwash, Vladan Radosavljevic, Zoran Obradovic

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

D²P²: database of disordered protein predictions.

Matt E. Oates, Pedro Romero, Takashi Ishida, 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

Early Diagnosis and Its Benefits in Sepsis Blood Purification Treatment.

Mohamed F. Ghalwash, Vladan Radosavljevic, Zoran Obradovic

Proceedings of the IEEE International Conference on Healthcare Informatics, 2013

Extraction of Interpretable Multivariate Patterns for Early Diagnostics.

Mohamed F. Ghalwash, Vladan Radosavljevic, Zoran Obradovic

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

Early classification of multivariate temporal observations by extraction of interpretable shapelets.

Mohamed F. Ghalwash, Zoran Obradovic

BMC Bioinform., 2012

Early classification of multivariate time series using a hybrid HMM/SVM model.

Mohamed F. Ghalwash, Dusan Ramljak, Zoran Obradovic

Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012