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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Blog Post number 1
Published:
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portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
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publications
Automated AI Detection Tool for Ankle Fractures Using X-Rays and Smart Devices
Published in Foot & Ankle Orthopaedics, 2023
Recommended citation: Nassour N, Acitores JM, Jang C, et al. Automated AI Detection Tool for Ankle Fractures Using X-Rays and Smart Devices. Foot & Ankle Orthopaedics. 2023;8(4). doi:10.1177/2473011423S00026
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TLab at #SMM4H 2024: Retrieval-Augmented Generation for ADE Extraction and Normalization
Published in Proceedings of the 9th Social Media Mining for Health Research and Applications (SMM4H 2024), 2024
SMM4H 2024 Task 1 is focused on the identification and standardization of Adverse Drug Events (ADEs) in tweets.
Recommended citation: Jacob Berkowitz, Apoorva Srinivasan, Jose Cortina, and Nicholas Tatonetti1. 2024. TLab at #SMM4H 2024: Retrieval-Augmented Generation for ADE Extraction and Normalization. In Proceedings of the 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks, pages 153–157, Bangkok, Thailand. Association for Computational Linguistics.
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Generalizable and Automated Classification of TNM Stage from Pathology Reports with External Validation
Published in Nature communications, 2024
We present a generalizable method for the automated classification of TNM stage from pathology report text.
Recommended citation: Kefeli, J., Berkowitz, J., Acitores Cortina, J.M. et al. Generalizable and automated classification of TNM stage from pathology reports with external validation. Nat Commun 15, 8916 (2024). https://doi.org/10.1038/s41467-024-53190-9
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Probing Large Language Model Hidden States for Adverse Drug Reaction Knowledge
Published in Artificial Intelligence in Medicine (AIME25), 2024
We evaluate the use of Gemma Scope SAEs to identify how LLMs store known facts involving adverse drug reactions (ADRs).
Recommended citation: Berkowitz, J. et al. (2025). Probing Large Language Model Hidden States for Adverse Drug Reaction Knowledge. In: Bellazzi, R., Juarez Herrero, J.M., Sacchi, L., Zupan, B. (eds) Artificial Intelligence in Medicine. AIME 2025. Lecture Notes in Computer Science(), vol 15734. Springer, Cham. https://doi.org/10.1007/978-3-031-95838-0_6
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Foundation Models for Translational Cancer Biology
Published in Annual Reviews, 2025
We examine the role of foundation models in domains relevant to cancer research, including natural language processing, computer vision, molecular biology, and cheminformatics.
Recommended citation: Tsang, Kevin K., Kivelson, Sophia, Acitores Cortina, Jose M., Kuchi, Aditi, Berkowitz, Jacob S., Liu, Hongyu, Srinivasan, Apoorva, Friedrich, Nadine A., Fatapour, Yasaman, Tatonetti, Nicholas P. Foundation Models for Translational Cancer Biology, Annual Review of Biomedical Data Science, Volume 8, 2025, https://doi.org/10.1146/annurev-biodatasci-103123-095633
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Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for’Complete Data’
Published in JMIR, 2025
In this study, we examined the race/ethnicity biases introduced by applying common filters to four clinical records databases.
Recommended citation: Acitores Cortina J, Fatapour Y, Brown K, Gisladottir U, Zietz M, Bear Don’t Walk IV O, Peter D, Berkowitz J, Friedrich N, Kivelson S, Kuchi A, Liu H, Srinivasan A, Tsang K, Tatonetti N Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for “Complete Data”: Observational Clinical Data Analysis JMIR Med Inform 2025;13:e67591 URL: https://medinform.jmir.org/2025/1/e67591 DOI: 10.2196/67591
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Biomedical Text Normalization through Generative Modeling
Published in Journal of Biomedical Informatics, 2025
In this study, we develop and assess text normalization pipelines built using large-language models.
Recommended citation: Jacob S. Berkowitz, Apoorva Srinivasan, Jose Miguel Acitores Cortina, Yasaman Fatapour, Nicholas P Tatonetti, Biomedical text normalization through generative modeling, Journal of Biomedical Informatics, Volume 167, 2025, 104850, ISSN 1532-0464, https://doi.org/10.1016/j.jbi.2025.104850.
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Enhancing EHR-based pancreatic cancer prediction with LLM-derived embeddings
Published in npj Digital Medicine, 2025
We developed a predictive model using large language model (LLM)-derived embeddings of medical condition for early pancreatic cancer detection.
Recommended citation: Park, J., Patterson, J., Acitores Cortina, J.M. et al. Enhancing EHR-based pancreatic cancer prediction with LLM-derived embeddings. npj Digit. Med. 8, 465 (2025). https://doi.org/10.1038/s41746-025-01869-8
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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