Enhancing cardiovascular risk prediction through AI-enabled calcium-omics

no code implementations • 23 Aug 2023 • Ammar Hoori, Sadeer Al-Kindi, Tao Hu, Yingnan Song, Hao Wu, Juhwan Lee, Nour Tashtish, Pingfu Fu, Robert Gilkeson, Sanjay Rajagopalan, David L. Wilson

We used a Cox model with elastic-net regularization on 2457 CT calcium score (CTCS) enriched for MACE events obtained from a large no-cost CLARIFY program (ClinicalTri-als. gov Identifier: NCT04075162).

Novel Radiomic Measurements of Tumor- Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers

no code implementations • 5 Oct 2022 • Nathaniel Braman, Prateek Prasanna, Kaustav Bera, Mehdi Alilou, Mohammadhadi Khorrami, Patrick Leo, Maryam Etesami, Manasa Vulchi, Paulette Turk, Amit Gupta, Prantesh Jain, Pingfu Fu, Nathan Pennell, Vamsidhar Velcheti, Jame Abraham, Donna Plecha, Anant Madabhushi

QuanTAV risk scores were prognostic of recurrence free survival in treatment cohorts chemotherapy for breast cancer (p=0. 002, HR=1. 25, 95% CI 1. 08-1. 44, C-index=. 66) and chemoradiation for NSCLC (p=0. 039, HR=1. 28, 95% CI 1. 01-1. 62, C-index=0. 66).

Experimental Design

Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: A multi-institutional validation study

no code implementations • 22 Jan 2020 • Nathaniel Braman, Mohammed El Adoui, Manasa Vulchi, Paulette Turk, Maryam Etesami, Pingfu Fu, Kaustav Bera, Stylianos Drisis, Vinay Varadan, Donna Plecha, Mohammed Benjelloun, Jame Abraham, Anant Madabhushi

In a retrospective study encompassing DCE-MRI data from a total of 157 HER2+ breast cancer patients from 5 institutions, we developed and validated a deep learning approach for predicting pathological complete response (pCR) to HER2-targeted NAC prior to treatment.