A. Rajkomar

发表

Ensuring Fairness in Machine Learning to Advance Health Equity

M. Howell, M. Chin, Michaela Hardt, 2018, Annals of Internal Medicine.

Structured Understanding of Assessment and Plans in Clinical Documentation

Doron Stupp, Amir Feder, A. Rajkomar, 2022, medRxiv.

Using Spatial and Temporal Mapping to Identify Nosocomial Disease Transmission of Clostridium difficile

Sara G. Murray, R. Cucina, G. Schmajuk, 2017, JAMA internal medicine.

Improving diagnostic reasoning to improve patient safety.

Alvin Rajkomar, Gurpreet Dhaliwal, A. Rajkomar, 2011, The Permanente journal.

Low Diagnostic Utility of Rechecking Hemoglobins Within 24 Hours in Hospitalized Patients.

C. McCulloch, M. Fang, A. Rajkomar, 2016, The American journal of medicine.

Predicting Inpatient Medication Orders From Electronic Health Record Data

Andrew M. Dai, Laura M. Vardoulakis, M. Howell, 2020, Clinical pharmacology and therapeutics.

Caring Wisely: A Program to Support Frontline Clinicians and Staff in Improving Healthcare Delivery and Reducing Costs.

A. Rajkomar, D. Grady, R. Gonzales, 2017, Journal of hospital medicine.

Improved Hierarchical Patient Classification with Language Model Pretraining over Clinical Notes

Andrew M. Dai, A. Rajkomar, Jonas Kemp, 2019, 1909.03039.

Deciphering clinical abbreviations with a privacy protecting machine learning system

Yuchen Liu, A. Rajkomar, Ming-Jun Chen, 2022, Nature Communications.

Large language models encode clinical knowledge

Hyung Won Chung, Martin G. Seneviratne, Vivek Natarajan, 2022, Nature.

High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks

Michael Blum, Alvin Rajkomar, John Mongan, 2016, Journal of Digital Imaging.

Scalable and accurate deep learning with electronic health records

Jeffrey Dean, Quoc V. Le, Andrew M. Dai, 2018, npj Digital Medicine.

Machine Learning in Medicine

Jeffrey Dean, Isaac Kohane, Alvin Rajkomar, 2019, The New England journal of medicine.

Association Between a Virtual Glucose Management Service and Glycemic Control in Hospitalized Adult Patients

D. Glidden, A. Rajkomar, M. Kohn, 2017, Annals of Internal Medicine.

Scalable and accurate deep learning with electronic health records

Quoc V. Le, Andrew M. Dai, Peter J. Liu, 2018, npj Digital Medicine.

What Happened to My Patient? An Educational Intervention to Facilitate Postdischarge Patient Follow-Up.

James D. Harrison, A. Rajkomar, G. Dhaliwal, 2017, Journal of graduate medical education.

Association Between Surgeon Scorecard Use and Operating Room Costs

L. Pitts, M. Lawton, R. Dudley, 2016, JAMA surgery.

Automatically Charting Symptoms From Patient-Physician Conversations Using Machine Learning.

Anjuli Kannan, Laura Vardoulakis, Alvin Rajkomar, 2019, JAMA internal medicine.

Electronic Order Volume as a Meaningful Component in Estimating Patient Complexity and Resident Physician Workload

M. Fang, A. Rajkomar, Nicole Van Groningen, 2018, Journal of hospital medicine.

Standardized Attending Rounds to Improve the Patient Experience: A Pragmatic Cluster Randomized Controlled Trial

James D. Harrison, M. Fang, A. Rajkomar, 2017, Journal of hospital medicine.

The association between discharge before noon and length of stay in medical and surgical patients.

A. Auerbach, A. Rajkomar, M. Mourad, 2016, Journal of hospital medicine.

Explaining an increase in predicted risk for clinical alerts

Gerardo Flores, Andrew M. Dai, Michael Howell, 2019, CHIL.

Next-generation audit and feedback for inpatient quality improvement using electronic health record data: a cluster randomised controlled trial

James D. Harrison, A. Rajkomar, S. Ranji, 2018, BMJ Quality & Safety.

Weighting Primary Care Patient Panel Size: A Novel Electronic Health Record-Derived Measure Using Machine Learning

Alvin Rajkomar, Kevin Grumbach, K. Grumbach, 2016, JMIR medical informatics.

Improved Patient Classification with Language Model Pretraining Over Clinical Notes pdf

Andrew M. Dai, Jonas Kemp, Alvin Rajkomar, 2019, ArXiv.

Weighting Primary Care Patient Panel Size: A Novel Electronic Health Record-Derived Measure Using Machine Learning

K. Grumbach, A. Rajkomar, J. Yim, 2016, JMIR medical informatics.

Semi-supervised Learning for Information Extraction from Dialogue

Anjuli Kannan, Kai Chen, Diana Jaunzeikare, 2018, INTERSPEECH.

Machine Learning in Medicine. Reply.

Isaac Kohane, Alvin Rajkomar, I. Kohane, 2019, The New England journal of medicine.

Publisher Correction: Large language models encode clinical knowledge.

Hyung Won Chung, Vivek Natarajan, D. Webster, 2023, Nature.