Sameer Antani, Ph.D.


Computational Health Research Branch


Building 38A, Room 10S-1004
8600 Rockville Pike
Bethesda, MD 20892


Research Topics

Dr. Antani is a senior researcher with contributing to advancing machine intelligence for automated, reliable, and interpretable clinical decision-making. In advancing reliable medical image-based artificial intelligence and machine learning (AI/ML), his current research focuses on characterizing data and their impact on AI prediction quality, making them interpretable and generalizable, and ultimately enabling them for disease screening, diagnostics, and treatment guidance. These interests are explored through computational health research in cardiopulmonary, infectious, cancer, genetic, and age-related diseases/conditions through multidisciplinary collaboration with experts in clinical medicine, medical informatics, statistics, and epidemiology at the NIH, and in academia and industry in the United States and worldwide. Dr. Antani holds scientific journal editorial board memberships, and various other leadership positions in scientific and technical professional societies (IEEE, SPIE). He is a Fellow of the American Institute of Medical and Biological Engineers (AIMBE) and a Senior Member of the IEEE and the SPIE, respectively. Bibliography is available here and on Google Scholar.

Selected Publications

  1. Zamzmi G, Rajaraman S, Hsu LY, Sachdev V, Antani S. Real-time echocardiography image analysis and quantification of cardiac indices. Med Image Anal. 2022;80:102438.
  2. Rajaraman S, Zamzmi G, Yang F, Xue Z, Jaeger S, Antani SK. Uncertainty Quantification in Segmenting Tuberculosis-Consistent Findings in Frontal Chest X-rays. Biomedicines. 2022;10(6).
  3. Guo P, Xue Z, Jeronimo J, Gage JC, Desai KT, Befano B, García F, Long LR, Schiffman M, Antani S. Network Visualization and Pyramidal Feature Comparison for Ablative Treatability Classification Using Digitized Cervix Images. J Clin Med. 2021;10(5).
  4. Xue Z, Novetsky AP, Einstein MH, Marcus JZ, Befano B, Guo P, Demarco M, Wentzensen N, Long LR, Schiffman M, Antani S. A demonstration of automated visual evaluation of cervical images taken with a smartphone camera. Int J Cancer. 2020;147(9):2416-2423.

Related Scientific Focus Areas

This page was last updated on Wednesday, April 3, 2024