Artificial Intelligence

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Lee, S. W., Huz, K., Gorelick, K., Li, J., Bina, T., Matsumura, S., Yin, N., Zhang, N., Anang, Y. N. A., Sachadava, S., Servin-DeMarrais, H. I., McMahon, D. J., Lu, H. H., Yin, M. T., & Wadhwa, S. (2025). Evaluation by dental professionals of an artificial intelligence-based application to measure alveolar bone loss. BMC Oral Health, 25(1). https://doi.org/10.1186/s12903-025-05677-0
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Zhou, A., Li, Z., Paul, W., Burlina, P., Mocharla, R., Joshi, N., Gu, S., Nanegrungsunk, O., Bressler, S., Cai, C. X., Alvin Liu, T. Y., Moini, H., Sepehrband, F., Bressler, N. M., & Kong, J. (2025). Estimating Visual Acuity With Spectacle Correction From Fundus Photos Using Artificial Intelligence. JAMA Network Open, 8(1), e2453770. https://doi.org/10.1001/jamanetworkopen.2024.53770
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Bunne, C., Roohani, Y., Rosen, Y., Gupta, A., Zhang, X., Roed, M., Alexandrov, T., AlQuraishi, M., Brennan, P., Burkhardt, D. B., Califano, A., Cool, J., Dernburg, A. F., Ewing, K., Fox, E. B., Haury, M., Herr, A. E., Horvitz, E., Hsu, P. D., … Quake, S. R. (2024). How to build the virtual cell with artificial intelligence: Priorities and opportunities. Cell, 187(25), 7045–7063. https://doi.org/10.1016/j.cell.2024.11.015
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Lyu, Y.-X., Fu, Q., Wilczok, D., Ying, K., King, A., Antebi, A., Vojta, A., Stolzing, A., Moskalev, A., Georgievskaya, A., Maier, A. B., Olsen, A., Groth, A., Simon, A. K., Brunet, A., Jamil, A., Kulaga, A., Bhatti, A., Yaden, B., … Bakula, D. (2024). Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity. Aging. https://doi.org/10.18632/aging.206135
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Benda, N., Desai, P., Reza, Z., Zheng, A., Kumar, S., Harkins, S., Hermann, A., Zhang, Y., Joly, R., Kim, J., Pathak, J., & Reading Turchioe, M. (2024). Patient Perspectives on AI for Mental Health Care: Cross-Sectional Survey Study. JMIR Mental Health, 11, e58462. https://doi.org/10.2196/58462
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Citkovitz, C., Graca, S., Anderson, B., Conboy, L. A., Gold, M. A., Hirsch, E., Lumiere, K., Phelps, S., Schnyer, R. N., Smith, R. J., & Taylor-Swanson, L. (2024). Acupuncture Practice-Based Research in the Age of Artificial Intelligence: Developments as of May, 2024. Journal of Integrative and Complementary Medicine, 30(8), 712–715. https://doi.org/10.1089/jicm.2024.0459
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Columbia Affiliation

Mehta, A., El-Najjar, D., Howell, H., Gupta, P., Arciero, E., Marigi, E. M., Parisien, R. L., & Trofa, D. P. (2024). Artificial Intelligence Models Are Limited in Predicting Clinical Outcomes Following Hip Arthroscopy: A Systematic Review. JBJS reviews, 12(8), e24.00087. https://doi.org/10.2106/JBJS.RVW.24.00087

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Faierstein, K., Fiman, M., Loutati, R., Rubin, N., Manor, U., Am-Shalom, A., Cohen-Shelly, M., Blank, N., Lotan, D., Zhao, Q., Schwammenthal, E., Klempfner, R., Zimlichman, E., Raanani, E., & Maor, E. (2024). Artificial Intelligence Assessment of Biological Age From Transthoracic Echocardiography: Discrepancies with Chronologic Age Predict Significant Excess Mortality. Journal of the American Society of Echocardiography, 37(8), 725–735. https://doi.org/10.1016/j.echo.2024.04.017
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Saqi, A., Liu, Y., Politis, M. G., Salvatore, M., & Jambawalikar, S. (2024). Combined expert-in-the-loop—random forest multiclass segmentation U-net based artificial intelligence model: evaluation of non-small cell lung cancer in fibrotic and non-fibrotic microenvironments. Journal of Translational Medicine, 22(1). https://doi.org/10.1186/s12967-024-05394-2
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Matsubayashi, C. O., Cheng, S., Hulchafo, I., Zhang, Y., Tada, T., Buxbaum, J. L., & Ochiai, K. (2024). Artificial intelligence for gastric cancer in endoscopy: From diagnostic reasoning to market. Digestive and Liver Disease, 56(7), 1156–1163. https://doi.org/10.1016/j.dld.2024.04.019
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Columbia Affiliation
Resch, D., Lo Gullo, R., Teuwen, J., Semturs, F., Hummel, J., Resch, A., & Pinker, K. (2024). AI-enhanced Mammography With Digital Breast Tomosynthesis for Breast Cancer Detection: Clinical Value and Comparison With Human Performance. Radiology: Imaging Cancer, 6(4). https://doi.org/10.1148/rycan.230149
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Gordon, E. R., Trager, M. H., Kontos, D., Weng, C., Geskin, L. J., Dugdale, L. S., & Samie, F. H. (2024). Ethical considerations for artificial intelligence in dermatology: a scoping review. British Journal of Dermatology, 190(6), 789–797. https://doi.org/10.1093/bjd/ljae040
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Sathe, T. S., Roshal, J., Naaseh, A., L’Huillier, J. C., Navarro, S. M., & Silvestri, C. (2024). How I GPT It: Development of Custom Artificial Intelligence (AI) Chatbots for Surgical Education. Journal of Surgical Education, 81(6), 772–775. https://doi.org/10.1016/j.jsurg.2024.03.004
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Elias, P., Jain, S. S., Poterucha, T., Randazzo, M., Lopez Jimenez, F., Khera, R., Perez, M., Ouyang, D., Pirruccello, J., Salerno, M., Einstein, A. J., Avram, R., Tison, G. H., Nadkarni, G., Natarajan, V., Pierson, E., Beecy, A., Kumaraiah, D., Haggerty, C., … Maddox, T. M. (2024). Artificial Intelligence for Cardiovascular Care—Part 1: Advances. Journal of the American College of Cardiology, 83(24), 2472–2486. https://doi.org/10.1016/j.jacc.2024.03.400
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Jain, S. S., Elias, P., Poterucha, T., Randazzo, M., Lopez Jimenez, F., Khera, R., Perez, M., Ouyang, D., Pirruccello, J., Salerno, M., Einstein, A. J., Avram, R., Tison, G. H., Nadkarni, G., Natarajan, V., Pierson, E., Beecy, A., Kumaraiah, D., Haggerty, C., … Maddox, T. M. (2024). Artificial Intelligence in Cardiovascular Care—Part 2: Applications. Journal of the American College of Cardiology, 83(24), 2487–2496. https://doi.org/10.1016/j.jacc.2024.03.401
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Salvador, T., Gu, L., Hay, J. L., Kurtansky, N. R., Masterson-Creber, R., Halpern, A. C., & Rotemberg, V. (2024). Consent and Identifiability for Patient Images in Research, Education, and Image-Based Artificial Intelligence. JAMA Dermatology, 160(4), 470. https://doi.org/10.1001/jamadermatol.2024.0084
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Columbia Affiliation
Zech, J. R., Santos, L., Staffa, S., Zurakowski, D., Rosenwasser, K. A., Tsai, A., Jaramillo, D., & Panzer, A. (2024). Lower Extremity Growth according to AI Automated Femorotibial Length Measurement on Slot-Scanning Radiographs in Pediatric Patients. Radiology, 311(1). https://doi.org/10.1148/radiol.231055
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Ranard, B. L., Park, S., Jia, Y., Zhang, Y., Alwan, F., Celi, L. A., & Lusczek, E. R. (2024). Minimizing bias when using artificial intelligence in critical care medicine. Journal of Critical Care, 82, 154796. https://doi.org/10.1016/j.jcrc.2024.154796
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Wei, Q., Yao, Z., Cui, Y., Wei, B., Jin, Z., & Xu, X. (2024). Evaluation of ChatGPT-generated medical responses: A systematic review and meta-analysis. Journal of Biomedical Informatics, 151, 104620. https://doi.org/10.1016/j.jbi.2024.104620
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Spotnitz, M., Idnay, B., Gordon, E. R., Shyu, R., Zhang, G., Liu, C., Cimino, J. J., & Weng, C. (2024). A Survey of Clinicians’ Views of the Utility of Large Language Models. Applied Clinical Informatics, 15(02), 306–312. CLOCKSS. https://doi.org/10.1055/a-2281-7092
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Yi, P. H., Garner, H. W., Hirschmann, A., Jacobson, J. A., Omoumi, P., Oh, K., Zech, J. R., & Lee, Y. H. (2024). Clinical Applications, Challenges, and Recommendations for Artificial Intelligence in Musculoskeletal and Soft-Tissue Ultrasound: AJR Expert Panel Narrative Review. American Journal of Roentgenology, 222(3). https://doi.org/10.2214/ajr.23.29530
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Desai, M., Ausk, K., Brannan, D., Chhabra, R., Chan, W., Chiorean, M., Gross, S. A., Girotra, M., Haber, G., Hogan, R. B., Jacob, B., Jonnalagadda, S., Iles-Shih, L., Kumar, N., Law, J., Lee, L., Lin, O., Mizrahi, M., Pacheco, P., … Sharma, P. (2024). Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial. American Journal of Gastroenterology, 119(7), 1383–1391. https://doi.org/10.14309/ajg.0000000000002664
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Ahimaz, P., Bergner, A. L., Florido, M. E., Harkavy, N., & Bhattacharyya, S. (2023). Genetic counselors’ utilization of ChatGPT in professional practice: A cross‐sectional study. American Journal of Medical Genetics Part A, 194(4). Portico. https://doi.org/10.1002/ajmg.a.63493
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Burry, N., Nakagawa, S., & Blinderman, C. D. (2024). “You Are Not Alone”: The Allure and Limitations of Artificial Intelligence in Serious Illness Communication. Journal of Palliative Medicine, 27(1), 7–9. https://doi.org/10.1089/jpm.2023.0471
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Samant, S., Bakhos, J. J., Wu, W., Zhao, S., Kassab, G. S., Khan, B., Panagopoulos, A., Makadia, J., Oguz, U. M., Banga, A., Fayaz, M., Glass, W., Chiastra, C., Burzotta, F., LaDisa, J. F., Iaizzo, P., Murasato, Y., Dubini, G., Migliavacca, F., … Chatzizisis, Y. S. (2023). Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions. JACC: Cardiovascular Interventions, 16(20), 2479–2497. https://doi.org/10.1016/j.jcin.2023.07.022
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Zech, J. R., Jaramillo, D., Altosaar, J., Popkin, C. A., & Wong, T. T. (2023). Artificial intelligence to identify fractures on pediatric and young adult upper extremity radiographs. Pediatric Radiology, 53(12), 2386–2397. https://doi.org/10.1007/s00247-023-05754-y
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Raghavendra, U., Gudigar, A., Paul, A., Goutham, T. S., Inamdar, M. A., Hegde, A., Devi, A., Ooi, C. P., Deo, R. C., Barua, P. D., Molinari, F., Ciaccio, E. J., & Acharya, U. R. (2023). Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives. Computers in Biology and Medicine, 163, 107063. https://doi.org/10.1016/j.compbiomed.2023.107063
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Palmieri, V., Montisci, A., Vietri, M. T., Colombo, P. C., Sala, S., Maiello, C., Coscioni, E., Donatelli, F., & Napoli, C. (2023). Artificial intelligence, big data and heart transplantation: Actualities. International Journal of Medical Informatics, 176, 105110. https://doi.org/10.1016/j.ijmedinf.2023.105110
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Yoon, S., Broadwell, P., Sun, F. F., De Planell-Saguer, M., & Davis, N. (2023). Application of Topic Modeling on Artificial Intelligence Studies as a Foundation to Develop Ethical Guidelines in African American Dementia Caregiving. Healthcare Transformation with Informatics and Artificial Intelligence. https://doi.org/10.3233/shti230553
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Sanguinetti, M., Silva Santos, L. H., Dourron, J., Alamón, C., Idiarte, J., Amillis, S., Pantano, S., & Ramón, A. (2022). Substrate Recognition Properties from an Intermediate Structural State of the UreA Transporter. International Journal of Molecular Sciences, 23(24), 16039. https://doi.org/10.3390/ijms232416039
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Ronquillo, C. E., Mitchell, J., Alhuwail, D., Peltonen, L.-M., Topaz, M., & Block, L. J. (2022). The Untapped Potential of Nursing and Allied Health Data for Improved Representation of Social Determinants of Health and Intersectionality in Artificial Intelligence Applications: A Rapid Review. Yearbook of Medical Informatics, 31(01), 094–099. CLOCKSS. https://doi.org/10.1055/s-0042-1742504
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Columbia Affiliation
Dercle, L., McGale, J., Sun, S., Marabelle, A., Yeh, R., Deutsch, E., Mokrane, F.-Z., Farwell, M., Ammari, S., Schoder, H., Zhao, B., & Schwartz, L. H. (2022). Artificial intelligence and radiomics: fundamentals, applications, and challenges in immunotherapy. Journal for ImmunoTherapy of Cancer, 10(9), e005292. https://doi.org/10.1136/jitc-2022-005292
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von Gerich, H., Moen, H., Block, L. J., Chu, C. H., DeForest, H., Hobensack, M., Michalowski, M., Mitchell, J., Nibber, R., Olalia, M. A., Pruinelli, L., Ronquillo, C. E., Topaz, M., & Peltonen, L.-M. (2022). Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence. International Journal of Nursing Studies, 127, 104153. https://doi.org/10.1016/j.ijnurstu.2021.104153
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Columbia Affiliation