Mohamed F. Ghalwash

Orcid: 0000-0002-3169-4346

Affiliations:
  • IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA
  • Temple University, Center for Data Analytics and Biomedicai Informatics, Philadelphia, PA, USA
  • Ain Shams University, Mathematics Department, Cairo, Egypt


According to our database1, Mohamed F. Ghalwash authored at least 38 papers between 2012 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes.
Artif. Intell. Medicine, March, 2023

2022
Human-centered explainability for life sciences, healthcare, and medical informatics.
Patterns, 2022

An Ontology for Fairness Metrics.
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.
CoRR, 2021

Disease Progression Modeling Workbench 360.
CoRR, 2021

Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge.
CoRR, 2021

G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime.
Proceedings of the Machine Learning for Health, 2021

Phenotypical ontology driven framework for multi-task learning.
Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

Simulating Screening for Risk of Childhood Diabetes: The Collaborative Open Outcomes tooL (COOL).
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.
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.
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.
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.
CoRR, 2020

G-Net: A Deep Learning Approach to G-computation for Counterfactual Outcome Prediction Under Dynamic Treatment Regimes.
CoRR, 2020

A Multi-Task Learning Approach to Personalized Progression Modeling.
Proceedings of the 8th IEEE International Conference on Healthcare Informatics, 2020

Predicting Type 1 Diabetes Onset using Novel Survival Analysis with Biomarker Ontology.
Proceedings of the AMIA 2020, 2020

Leveraging Longitudinal Autoantibody for Phenotyping of Progression Rates to Type 1 Diabetes.
Proceedings of the AMIA 2020, 2020

Finding Causal Mechanistic Drug-Drug Interactions from Observational Data.
Proceedings of the AMIA 2020, 2020

2019
Temporal Graph Regression via Structure-Aware Intrinsic Representation Learning.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

eXITs: An Ensemble Approach for Imputing Missing EHR Data.
Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019

2018
Estimating Causal Multi-Drug-Drug Interaction for Adverse Drug Reactions.
Proceedings of the AMIA 2018, 2018

2017
Minimum redundancy maximum relevance feature selection approach for temporal gene expression data.
BMC Bioinform., 2017

Ranking Based Multitask Learning of Scoring Functions.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Cost Sensitive Time-Series Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Exploiting Electronic Health Records to Mine Drug Effects on Laboratory Test Results.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Continuous Conditional Dependency Network for Structured Regression.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Structured feature selection using coordinate descent optimization.
BMC Bioinform., 2016

Joint Learning of Representation and Structure for Sparse Regression on Graphs.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

A fast structured regression for large networks.
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.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Patient-specific early classification of multivariate observations.
Int. J. Data Min. Bioinform., 2015

False alarm suppression in early prediction of cardiac arrhythmia.
Proceedings of the 15th IEEE International Conference on Bioinformatics and Bioengineering, 2015

2014
Utilizing temporal patterns for estimating uncertainty in interpretable early decision making.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013
D<sup>2</sup>P<sup>2</sup>: database of disordered protein predictions.
Nucleic Acids Res., 2013

Early Diagnosis and Its Benefits in Sepsis Blood Purification Treatment.
Proceedings of the IEEE International Conference on Healthcare Informatics, 2013

Extraction of Interpretable Multivariate Patterns for Early Diagnostics.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
Early classification of multivariate temporal observations by extraction of interpretable shapelets.
BMC Bioinform., 2012

Early classification of multivariate time series using a hybrid HMM/SVM model.
Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012


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