Deep learning with uncertainty quantification for predicting segmentation Dice coefficient of prostate cancer biopsy images

Audrey Xie, El Fatimi E, Ghosal S, Shah P*

( *Senior author supervising research)

Accepted: 2024 23rd IEEE ICMLA Machine Learning Conference

Uncertainty quantified deep learning and regression analysis framework for clinical regions of interest segmentation in skin lesions

El Houcine El Fatimi, Shah P*

( *Senior author supervising research)

Accepted: 2024 23rd IEEE ICMLA Machine Learning Conference

Responsible deep learning for software as a medical device

Pratik Shah*, Lester J, Delfino J, Pai V

(*Senior author supervising research)

arXiv:2312.13333 [eess.IV]

A deep-learning toolkit for visualization and interpretation of segmented medical images

Sambuddha Ghosal and Shah P*

( *Senior author supervising research)

Cell Reports Methods 1, 100107, 2021

Uncertainty quantified deep learning for predicting dice coefficient of digital histopathology image segmentation

Sambuddha Ghosal, Xie A, Shah P*

( *Senior author supervising research)

arXiv:2011.05791 [stat.ML]

Automated end-to-end deep learning framework for classification and tumor localization from native non-stained pathology images

Akram Bayat, Anderson C, Shah P*^♯

(*Senior author supervising research, ^♯Selected for Deep-dive spotlight session)

SPIE Proceedings. DOI: 10.1117/12.2582303

Use of deep learning to develop and analyze computational hematoxylin and eosin staining of prostate core biopsy images for tumor diagnosis

Aman Rana, Lowe A, Lithgow M, Horback K, Janovitz T, Da Silva A, Tsai H, Shanmugam V, Bayat A, Shah P*

(*Senior author supervising research)

JAMA Network. DOI: 10.1001/jamanetworkopen.2020.5111

Artificial neural networks detect and classify hematologic malignancies or solid tumors using electronic medical records prior to clinical diagnosis

Yujia Zhou, Barnes C, Magoc T, Lipori G, Shah P, Cogle CR

Published at 61st American Society of Hematology Annual Meeting, Orlando, FL

Data science in clinical pharmacology and drug development for improving health outcomes in patients

Pratik Shah, Peck R, Vamvakas S, van der Graaf, Piet H

Clinical Pharmacology and Therapeutics. PMID: 32202650

Improving cancer diagnosis and care: clinical application of computational methods in precision oncology

Proceedings of a Workshop, National Academies of Sciences, Engineering, and Medicine. Washington, DC: The National Academies Press. PMID: 31386317

Artificial intelligence and machine learning in clinical development: a translational perspective

Pratik Shah* et al.

(*Corresponding author)

Nature Digital Medicine. DOI: 10.1038/s41746-019-0148-3

Artificial Intelligence for clinical trial design

Stefan Harrer, Shah P, Antony P, Hu J

Trends in Pharmacological Sciences. PMID: 31326235

Automated process incorporating machine learning segmentation and correlation of oral diseases with systemic health

Gregory Yauney, Rana A, Javia P, Wong L, Muftu A, Shah P*

(*Senior author supervising research)

41st IEEE International Engineering in Medicine and Biology Conference. DOI: 10.1109/EMBC.2019.8857965

Reinforcement learning with action-derived rewards for chemotherapy and clinical trial dosing regimen selection

Gregory Yauney, Shah P*

(*Senior author supervising research)

Proceedings of the 3rd Machine Learning for Healthcare Conference. PMLR 85:161-226

Computational histological staining and destaining of prostate core biopsy RGB images with generative adversarial neural networks

Aman Rana, Yauney G, Lowe A, Shah P*

(*Senior author supervising research)

17th IEEE International Conference of Machine Learning and Applications. DOI: 10.1109/ICMLA.2018.00133

Machine learning algorithms for classification of microcirculation images from septic and non-septic patients

Perikumar Javia, Rana A, Shapiro NI, Shah P*

(*Senior author supervising research)

17th IEEE International Conference of Machine Learning and Applications. DOI: 10.1109/ICMLA.2018.00097

Convolutional neural network for combined classification of fluorescent biomarkers and expert annotations using white light images

Gregory Yauney, Angelino K, Edlund D, Shah P*^♯

(*Senior author supervising research, ^♯Selected for oral presentation)

17^th annual IEEE International Conference on BioInformatics and BioEngineering. DOI: 10.1109/BIBE.2017.00-37

Automated segmentation of gingival diseases from oral images

Aman Rana, Yauney G, Wong L, Muftu A, Shah P*

(*Senior author supervising research)

IEEE-NIH 2017 Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies. DOI: 10.1109/HIC.2017.8227605