Frank M. Sanfilippo

According to our database, Frank M. Sanfilippo authored at least 11 papers between 2015 and 2023.

Collaborative distances:

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

2023

Deep learning model to predict exercise stress test results: Optimizing the diagnostic test selection strategy and reduce wastage in suspected coronary artery disease patients.

Juan Lu, Jonathon Stewart, Mohammed Bennamoun, Adrian Goudie, Jason Eshraghian, Abdul Ihdayhid, Frank M. Sanfilippo, Gary R. Small, Benjamin J. W. Chow, Girish Dwivedi

Comput. Methods Programs Biomed., October, 2023

Inflating 2D convolution weights for efficient generation of 3D medical images.

Yanbin Liu, Girish Dwivedi, Farid Boussaïd, Frank M. Sanfilippo, Makoto Yamada, Mohammed Bennamoun

Comput. Methods Programs Biomed., October, 2023

Multitask Deep Learning for Accurate Risk Stratification and Prediction of Next Steps for Coronary CT Angiography Patients.

Juan Lu, Mohammed Bennamoun, Jonathon Stewart, Jason Kamran Eshraghian, Yanbin Liu, Benjamin J. W. Chow, Frank M. Sanfilippo, Girish Dwivedi

CoRR, 2023

Analysis and Evaluation of Explainable Artificial Intelligence on Suicide Risk Assessment.

Hao Tang, Aref Miri Rekavandi, Dharjinder Rooprai, Girish Dwivedi, Frank M. Sanfilippo, Farid Boussaïd, Mohammed Bennamoun

CoRR, 2023

2022

A reinforcement learning-based approach for imputing missing data.

Saqib Ejaz Awan, Mohammed Bennamoun, Ferdous Sohel, Frank M. Sanfilippo, Girish Dwivedi

Neural Comput. Appl., 2022

Performance of multilabel machine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation.

Juan Lu, Rebecca Hutchens, Joseph Hung, Mohammed Bennamoun, Brendan McQuillan, Tom Briffa, Ferdous Sohel, Kevin Murray, Jonathon Stewart, Benjamin J. W. Chow, Frank M. Sanfilippo, Girish Dwivedi

Comput. Biol. Medicine, 2022

2021

Imputation of missing data with class imbalance using conditional generative adversarial networks.

Saqib Ejaz Awan, Mohammed Bennamoun, Ferdous Sohel, Frank M. Sanfilippo, Girish Dwivedi

Neurocomputing, 2021

Explainable Artificial Intelligence for Pharmacovigilance: What Features Are Important When Predicting Adverse Outcomes?

Isaac Ronald Ward, Ling Wang, Juan Lu, Mohammed Bennamoun, Girish Dwivedi, Frank M. Sanfilippo

CoRR, 2021

Explainable artificial intelligence for pharmacovigilance: What features are important when predicting adverse outcomes?

Isaac Ronald Ward, Ling Wang, Juan Lu, Mohammed Bennamoun, Girish Dwivedi, Frank M. Sanfilippo

Comput. Methods Programs Biomed., 2021

2020

Improving patient-provider communication about chronic pain: development and feasibility testing of a shared decision-making tool.

Nananda F. Col, Stephen Hull, Vicky Springmann, Long Ngo, Ernie Merritt, Susan Gold, Michael Sprintz, Noel Genova, Noah Nesin, Brenda Tierman, Frank M. Sanfilippo, Richard Entel, Lori Pbert

BMC Medical Informatics Decis. Mak., 2020

2015

A comparison of multivariate and univariate time series approaches to modelling and forecasting emergency department demand in Western Australia.

Patrick Aboagye-Sarfo, Qun Mai, Frank M. Sanfilippo, David B. Preen, Louise M. Stewart, Daniel M. Fatovich

J. Biomed. Informatics, 2015