Join the “Artificial Intelligence (AI) in Health” Journal Club to stay up to date on the latest in artificial intelligence research and its applications for biomedicine and health. The monthly meetings encourage active discussions about the application and impact of AI in healthcare with the goal of inspiring collaborative research.
The group meets online at noon on the third Tuesday of each month. All interested in AI are welcome, including those from other institutions and the community.
Click to register for upcoming AI in Health Journal Club meetings.
For more information please contact Assistant Professor of Biomedical Informatics Jonathan Bona, Ph.D., at JPBona@uams.edu.
Schedule
| Date | Topic |
|---|---|
| October 17, 2023 | Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Discussion lead by Fred Prior, Ph.D., Distinguished Professor and Chair, Department of Biomedical Informatics Paper: Campanella G, Hanna MG, Geneslaw L, Miraflor A, Werneck Krauss Silva V, Busam KJ, Brogi E, Reuter VE, Klimstra DS, Fuchs TJ. Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nature medicine. 2019 Aug;25(8):1301-9. |
| August 15, 2023 | Machine Learning–Assisted Recurrence Prediction for Patients With Early-Stage Non–Small-Cell Lung Cancer Discussion lead by Jim Chen, MD, Hematology/Oncology Fellow PGY6, UAMS. Paper: Janik A, Torrente M, Costabello L, Calvo V, Walsh B, Camps C, Mohamed SK, Ortega AL, Nováček V, Massutí B, Minervini P. Machine Learning–Assisted Recurrence Prediction for Patients With Early-Stage Non–Small-Cell Lung Cancer. JCO Clinical Cancer Informatics. 2023 Jul;7:e2200062. https://ascopubs.org/doi/full/10.1200/CCI.22.00062 |
| July 18, 2023 | Natural language processing of radiology requests and reports of chest imaging Discussion lead by Michael Rutherford, M.S., Ph.D. Candidate, Instructor UAMS Biomedical Informatics. Paper: Olthof AW, van Ooijen PM, Cornelissen LJ. The natural language processing of radiology requests and reports of chest imaging: Comparing five transformer models’ multilabel classification and a proof-of-concept study. Health Informatics Journal. 2022 Oct 10;28(4):14604582221131198. https://journals.sagepub.com/doi/pdf/10.1177/14604582221131198 |
| May | GPT and Large Generative Language Models for AI in Health Discussion lead by Daniel Liu, M.D., M.A., Clinical Informaticist/Pediatric Hospitalist, ACH Assistant Professor of Pediatrics, UAMS Paper: Lee P, Bubeck S, Petro J. Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine. New England Journal of Medicine. 2023 Mar 30;388(13):1233-9. https://www.nejm.org/doi/10.1056/NEJMsr2214184 Supplementary reading: Gozalo-Brizuela R, Garrido-Merchan EC. ChatGPT is not all you need. A State of the Art Review of large Generative AI models. arXiv preprint arXiv:2301.04655. 2023 Jan 11. https://arxiv.org/abs/2301.04655 |
| April 18, 2023 | Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence Discussion lead by Azriel Stinson, DO, Clinical Informatics Fellow, UAMS & ACH Paper: Liang, H., Tsui, B.Y., Ni, H. et al. Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence. Nat Med 25, 433–438 (2019). https://doi.org/10.1038/s41591-018-0335-9 |
| March 21, 2023 | medigan: a Python library of pretrained generative models for medical image synthesis Discussion lead by Fred Prior, Ph.D., Distinguished Professor and Chair, Department of Biomedical Informatics Paper: Richard Osuala, Grzegorz Skorupko, Noussair Lazrak, Lidia Garrucho, Eloy García, Smriti Joshi, Socayna Jouide, Michael Rutherford, Fred Prior, Kaisar Kushibar, Oliver Díaz, Karim Lekadir, “medigan: a Python library of pretrained generative models for medical image synthesis,” J. Med. Imag. 10(6) 061403 (20 February 2023) https://doi.org/10.1117/1.JMI.10.6.061403 |
| February 21, 2023 | Meeting the Moment: Addressing Barriers and Facilitating Clinical Adoption of Artificial Intelligence in Medical Diagnosis Discussion lead by Salem AlGhamdi, M.D., Clinical Informatics Fellow. Paper: Adler-Milstein J, Aggarwal N, Ahmed M, Castner J, Evans BJ, Gonzalez AA, James CA, Lin S, Mandl KD, Matheny ME, Sendak MP, Shachar C, Williams A. Meeting the Moment: Addressing Barriers and Facilitating Clinical Adoption of Artificial Intelligence in Medical Diagnosis. NAM Perspect. 2022 Sep 29;2022:10.31478/202209c. doi: 10.31478/202209c. PMID: 36713769; PMCID: PMC9875857. |
| January 17, 2023 | Explainable Artificial Intelligence Models Using Real-world Electronic Health Record Data. Discussion lead by Obeid Shafi, M.D., Clinical Informatics Fellow. Paper: Seyedeh Neelufar Payrovnaziri, Zhaoyi Chen, Pablo Rengifo-Moreno, Tim Miller, Jiang Bian, Jonathan H Chen, Xiuwen Liu, Zhe He, Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review, Journal of the American Medical Informatics Association, Volume 27, Issue 7, July 2020, Pages 1173–1185, https://doi.org/10.1093/jamia/ocaa053 |
| November 15, 2022 | Biomedical Ontologies to Guide AI Development in Radiology. Discussion lead by Mathias Brochhausen, Ph.D., Professor of Biomedical Informatics,. Paper: Filice RW, Kahn CE Jr. Biomedical Ontologies to Guide AI Development in Radiology. J Digit Imaging. 2021 Dec;34(6):1331-1341. doi: 10.1007/s10278-021-00527-1. Epub 2021 Nov 1. Erratum in: J Digit Imaging. 2022 Oct;35(5):1419. PMID: 34724143; PMCID: PMC8669056. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669056/ |
| October 20, 2022 | Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection. Discussion lead by Brian Delavan, M.P.H. Paper: Captur G, Moon JC, Topriceanu CC, Joy G, Swadling L, Hallqvist J, Doykov I, Patel N, Spiewak J, Baldwin T, Hamblin M. Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection. eBioMedicine. 2022 Sep 28:104293. https://doi.org/10.1016/j.ebiom.2022.104293 |
| September 20, 2022 | Artificial Intelligence in Health and Medicine. Discussion lead by Jonathan Bona, Ph.D., Assistant Professor of Biomedical Informatics. Paper: Rajpurkar, P., Chen, E., Banerjee, O. et al. AI in health and medicine. Nat Med 28, 31–38 (2022). https://doi.org/10.1038/s41591-021-01614-0 |