Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64697, first published .
A Deep Learning–Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records

A Deep Learning–Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records

A Deep Learning–Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records

Gowtham Varma   1 , MBBS ;   Rohit Kumar Yenukoti   1 , MBBS ;   Praveen Kumar M   1 , MD, DM ;   Bandlamudi Sai Ashrit   1 , MBBS ;   K Purushotham   1 , MBBS ;   C Subash   1 , MBBS ;   Sunil Kumar Ravi   1 , MBBS ;   Verghese Kurien   1 , MBBS ;   Avinash Aman   2 , BTech ;   Mithun Manoharan   1 , MBBS, MMST ;   Shashank Jaiswal   2 , B.Tech ;   Akash Anand   2 , BE ;   Rakesh Barve   2 , BTech, PhD ;   Viswanathan Thiagarajan   2 , B.Tech ;   Patrick Lenehan   3 , MD, PhD ;   Scott A Soefje   4 , BCOP, MBA, PharmD ;   Venky Soundararajan   3 , PhD

1 Department of Clinical Sciences, Nference, Bangalore, India

2 Department of Data Science and Engineering, Nference, Bangalore, India

3 Department of Clinical Sciences, Nference, Cambridge, MA, United States

4 Department of Pharmacy, Director of Pharmacy, Mayo Clinic, Rochester, MN, United States

Corresponding Author:

  • Praveen Kumar M, MD, DM
  • Department of Clinical Sciences
  • Nference
  • 4th Floor, Indiqube, Golf View Campus Tower-2, 22, 3rd Cross Rd, Murugeshpalya, S R Layout
  • Bangalore 560017
  • India
  • Phone: 91 8728831787
  • Email: pkumar@nference.net