AI in health and medicine von Rajpurkar, Pranav, Chen, Emma, Banerjee, Oishi, Topol, Eric J.

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The Current and Future State of AI Interpretation of Medical Images von Rajpurkar, Pranav, Lungren, Matthew P.

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Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network von Hannun, Awni Y., Rajpurkar, Pranav, Haghpanahi, Masoumeh, Tison, Geoffrey H., Bourn, Codie, Turakhia, Mintu P., Ng, Andrew Y.

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AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining von Rajpurkar, Pranav, Park, Allison, Irvin, Jeremy, Chute, Chris, Bereket, Michael, Mastrodicasa, Domenico, Langlotz, Curtis P., Lungren, Matthew P., Ng, Andrew Y., Patel, Bhavik N.

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Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning von Tiu, Ekin, Talius, Ellie, Patel, Pujan, Langlotz, Curtis P., Ng, Andrew Y., Rajpurkar, Pranav

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Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists von Rajpurkar, Pranav, Irvin, Jeremy, Ball, Robyn L, Zhu, Kaylie, Yang, Brandon, Mehta, Hershel, Duan, Tony, Ding, Daisy, Bagul, Aarti, Langlotz, Curtis P, Patel, Bhavik N, Yeom, Kristen W, Shpanskaya, Katie, Blankenberg, Francis G, Seekins, Jayne, Amrhein, Timothy J, Mong, David A, Halabi, Safwan S, Zucker, Evan J, Ng, Andrew Y, Lungren, Matthew P

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PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging von Huang, Shih-Cheng, Kothari, Tanay, Banerjee, Imon, Chute, Chris, Ball, Robyn L., Borus, Norah, Huang, Andrew, Patel, Bhavik N., Rajpurkar, Pranav, Irvin, Jeremy, Dunnmon, Jared, Bledsoe, Joseph, Shpanskaya, Katie, Dhaliwal, Abhay, Zamanian, Roham, Ng, Andrew Y., Lungren, Matthew P.

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Impact of a deep learning assistant on the histopathologic classification of liver cancer von Kiani, Amirhossein, Uyumazturk, Bora, Rajpurkar, Pranav, Wang, Alex, Gao, Rebecca, Jones, Erik, Yu, Yifan, Langlotz, Curtis P., Ball, Robyn L., Montine, Thomas J., Martin, Brock A., Berry, Gerald J., Ozawa, Michael G., Hazard, Florette K., Brown, Ryanne A., Chen, Simon B., Wood, Mona, Allard, Libby S., Ylagan, Lourdes, Ng, Andrew Y., Shen, Jeanne

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Foundation models for generalist medical artificial intelligence von Moor, Michael, Banerjee, Oishi, Abad, Zahra Shakeri Hossein, Krumholz, Harlan M., Leskovec, Jure, Topol, Eric J., Rajpurkar, Pranav

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Automated coronary calcium scoring using deep learning with multicenter external validation von Eng, David, Chute, Christopher, Khandwala, Nishith, Rajpurkar, Pranav, Long, Jin, Shleifer, Sam, Khalaf, Mohamed H., Sandhu, Alexander T., Rodriguez, Fatima, Maron, David J., Seyyedi, Saeed, Marin, Daniele, Golub, Ilana, Budoff, Matthew, Kitamura, Felipe, Takahashi, Marcelo Straus, Filice, Ross W., Shah, Rajesh, Mongan, John, Kallianos, Kimberly, Langlotz, Curtis P., Lungren, Matthew P., Ng, Andrew Y., Patel, Bhavik N.

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CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV von Rajpurkar, Pranav, O’Connell, Chloe, Schechter, Amit, Asnani, Nishit, Li, Jason, Kiani, Amirhossein, Ball, Robyn L., Mendelson, Marc, Maartens, Gary, van Hoving, Daniël J., Griesel, Rulan, Ng, Andrew Y., Boyles, Tom H., Lungren, Matthew P.

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Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy: A Machine Learning Experiment to Estimate Treatment Effects from Randomized Trial Da... von Duan, Tony, Rajpurkar, Pranav, Laird, Dillon, Ng, Andrew Y., Basu, Sanjay

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Human–machine partnership with artificial intelligence for chest radiograph diagnosis von Patel, Bhavik N., Rosenberg, Louis, Willcox, Gregg, Baltaxe, David, Lyons, Mimi, Irvin, Jeremy, Rajpurkar, Pranav, Amrhein, Timothy, Gupta, Rajan, Halabi, Safwan, Langlotz, Curtis, Lo, Edward, Mammarappallil, Joseph, Mariano, A. J., Riley, Geoffrey, Seekins, Jayne, Shen, Luyao, Zucker, Evan, Lungren, Matthew P.

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Benchmarking saliency methods for chest X-ray interpretation von Saporta, Adriel, Gui, Xiaotong, Agrawal, Ashwin, Pareek, Anuj, Truong, Steven Q. H., Nguyen, Chanh D. T., Ngo, Van-Doan, Seekins, Jayne, Blankenberg, Francis G., Ng, Andrew Y., Lungren, Matthew P., Rajpurkar, Pranav

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Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments von Irvin, Jeremy A, Kondrich, Andrew A, Ko, Michael, Rajpurkar, Pranav, Haghgoo, Behzad, Landon, Bruce E, Phillips, Robert L, Petterson, Stephen, Ng, Andrew Y, Basu, Sanjay

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DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set von Vrabac, Damir, Smit, Akshay, Rojansky, Rebecca, Natkunam, Yasodha, Advani, Ranjana H., Ng, Andrew Y., Fernandez-Pol, Sebastian, Rajpurkar, Pranav

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Predicting patient decompensation from continuous physiologic monitoring in the emergency department von Sundrani, Sameer, Chen, Julie, Jin, Boyang Tom, Abad, Zahra Shakeri Hossein, Rajpurkar, Pranav, Kim, David

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Autonomous AI systems in the face of liability, regulations and costs von Saenz, Agustina D., Harned, Zach, Banerjee, Oishi, Abràmoff, Michael D., Rajpurkar, Pranav

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Reimbursement in the age of generalist radiology artificial intelligence von Dogra, Siddhant, Silva, Ezequiel “Zeke”, Rajpurkar, Pranav

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Publisher Correction: Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network von Hannun, Awni Y., Rajpurkar, Pranav, Haghpanahi, Masoumeh, Tison, Geoffrey H., Bourn, Codie, Turakhia, Mintu P., Ng, Andrew Y.

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