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Sameer Antani, PhD

About

Picture of Sameer Antani, PhD

Sameer Antani, PhD

Tenure Track Investigator, Computational Health Research Branch

Research in reliable, reproducible, and interpretable multimodal machine learning and artificial intelligence using medical images and clinical data to advance health.

Contact Information

Building 38A, 8600 Rockville Pike MSC 6075 Bethesda, MD 20894

Tel: (301) 435-3218

sameer.antani@nih.gov

Research Interests

Dr. Sameer Antani is a Principal Investigator (Tenure-Track) in the Division of Intramural Research at the National Library of Medicine, part of the National Institutes of Health. He earned his PhD and MEng in Computer Science and Engineering from the Pennsylvania State University and his BE (First Class with Distinction) in Computer Engineering from the Savitribai Phule Pune University (formerly University of Pune), India. His research uses medical imaging and clinical data for novel multimodal machine learning (ML) and artificial intelligence (AI) algorithms toward developing reliable, reproducible, and interpretable prediction models with applications in disease screening, diagnostics, risk analysis, and treatment. Dr. Antani is a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), Fellow of Institute of Electrical and Electronics Engineers (IEEE), and Senior Member of the SPIE.

Publications

Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani S. Semantically redundant training data removal and deep model classification performance: A study with chest X-rays. Comput Med Imaging Graph. 2024 Jul;115:102379. doi: 10.1016/j.compmedimag.2024.102379. Epub 2024 Apr 9. PubMed PMID: 38608333; PubMed Central PMCID: PMC11144082.

Spirnak JR, Antani S. The Need for Artificial Intelligence Curriculum in Military Medical Education. Mil Med. 2024 May 18;189(5-6):954-958. doi: 10.1093/milmed/usad412. PubMed PMID: 37864817; PubMed Central PMCID: PMC11439989.

Xue Z, Oguguo T, Yu KJ, Chen TC, Hua CH, Kang CJ, Chien CY, Tsai MH, Wang CP, Chaturvedi AK, Antani S. Cleaning and Harmonizing Medical Image Data for Reliable AI: Lessons Learned from Longitudinal Oral Cancer Natural History Study Data. Proc SPIE Int Soc Opt Eng. 2024 Feb;12931. doi: 10.1117/12.3005875. Epub 2024 Apr 2. PubMed PMID: 38774479; PubMed Central PMCID: PMC11107840.

Rajaraman S, Zamzmi G, Yang F, Liang Z, Xue Z, Antani S. Uncovering the effects of model initialization on deep model generalization: A study with adult and pediatric chest X-ray images. PLOS Digit Health. 2024 Jan;3(1):e0000286. doi: 10.1371/journal.pdig.0000286. eCollection 2024 Jan. PubMed PMID: 38232121; PubMed Central PMCID: PMC10793885.

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