Das, Ritankar

Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach

Desautels, T., Calvert, J., Hoffman, J., Jay, M., Kerem, Y., Shieh, L., Shimabukuro, D., Chettipally, U., Feldman, M. D., Barton, C., et al. (2016) · JMIR Medical Informatics

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 509

Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: A randomised clinical trial.

Shimabukuro, D. W., Barton, C. W., Feldman, M. D., Mataraso, S. J., & Das, R. (2017) · BMJ Open Respiratory Research

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 382

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU

Mao, Q., Jay, M., Hoffman, J. L., Calvert, J., Barton, C., Shimabukuro, D., Shieh, L., Chettipally, U., Fletcher, G., Kerem, Y., et al. (2018) · BMJ Open

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 336

A computational approach to early sepsis detection

Calvert, J. S., Price, D. A., Chettipally, U. K., Barton, C. W., Feldman, M. D., Hoffman, J. L., Jay, M., & Das, R. (2016) · Computers in Biology and Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 244

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs

Barton, C., Chettipally, U., Zhou, Y., Jiang, Z., Lynn-Palevsky, A., Le, S., Calvert, J., & Das, R. (2019) · Computers in Biology and Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 175

Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units

McCoy, A., & Das, R. (2017) · BMJ Open Quality

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 148

Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals

Burdick, H., Pino, E., Gabel-Comeau, D., McCoy, A., Gu, C., Roberts, J., Le, S., Slote, J., Pellegrini, E., Green-Saxena, A., et al. (2020) · BMJ Health & Care Informatics

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 80

High-performance detection and early prediction of septic shock for alcohol-use disorder patients

Calvert, J., Desautels, T., Chettipally, U., Barton, C., Hoffman, J., Jay, M., Mao, Q., Mohamadlou, H., & Das, R. (2016) · Annals of Medicine & Surgery

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 62

Evaluating a sepsis prediction machine learning algorithm in the emergency department and intensive care unit: a before and after comparative study

Burdick, H., Pino, E., Gabel-Comeau, D., Gu, C., Huang, H., Lynn-Palevsky, A., & Das, R. (2017) · bioRxiv (Cold Spring Harbor Laboratory)

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 20