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Items: 20

1.

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.

Comput Biol Med. 2019 Jun;109:79-84. doi: 10.1016/j.compbiomed.2019.04.027. Epub 2019 Apr 24.

PMID:
31035074
2.

Machine-Learning-Based Laboratory Developed Test for the Diagnosis of Sepsis in High-Risk Patients.

Calvert J, Saber N, Hoffman J, Das R.

Diagnostics (Basel). 2019 Feb 13;9(1). pii: E20. doi: 10.3390/diagnostics9010020.

3.

Computational neuroscience and neuroinformatics: Recent progress and resources.

Nayak L, Dasgupta A, Das R, Ghosh K, De RK.

J Biosci. 2018 Dec;43(5):1037-1054. Review.

4.

Prediction of Acute Kidney Injury With a Machine Learning Algorithm Using Electronic Health Record Data.

Mohamadlou H, Lynn-Palevsky A, Barton C, Chettipally U, Shieh L, Calvert J, Saber NR, Das R.

Can J Kidney Health Dis. 2018 Jun 8;5:2054358118776326. doi: 10.1177/2054358118776326. eCollection 2018.

6.

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

Shimabukuro DW, Barton CW, Feldman MD, Mataraso SJ, Das R.

BMJ Open Respir Res. 2017 Nov 9;4(1):e000234. doi: 10.1136/bmjresp-2017-000234. eCollection 2017.

7.

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 JL, Calvert J, Barton C, Shimabukuro D, Shieh L, Chettipally U, Fletcher G, Kerem Y, Zhou Y, Das R.

BMJ Open. 2018 Jan 26;8(1):e017833. doi: 10.1136/bmjopen-2017-017833.

8.

Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: a cross-sectional machine learning approach.

Desautels T, Das R, Calvert J, Trivedi M, Summers C, Wales DJ, Ercole A.

BMJ Open. 2017 Sep 15;7(9):e017199. doi: 10.1136/bmjopen-2017-017199.

9.

Machine learning landscapes and predictions for patient outcomes.

Das R, Wales DJ.

R Soc Open Sci. 2017 Jul 26;4(7):170175. doi: 10.1098/rsos.170175. eCollection 2017 Jul.

10.

Using Transfer Learning for Improved Mortality Prediction in a Data-Scarce Hospital Setting.

Desautels T, Calvert J, Hoffman J, Mao Q, Jay M, Fletcher G, Barton C, Chettipally U, Kerem Y, Das R.

Biomed Inform Insights. 2017 Jun 12;9:1178222617712994. doi: 10.1177/1178222617712994. eCollection 2017.

11.

Energy landscapes for machine learning.

Ballard AJ, Das R, Martiniani S, Mehta D, Sagun L, Stevenson JD, Wales DJ.

Phys Chem Chem Phys. 2017 May 24;19(20):12585-12603. doi: 10.1039/c7cp01108c.

PMID:
28367548
12.

Cost and mortality impact of an algorithm-driven sepsis prediction system.

Calvert J, Hoffman J, Barton C, Shimabukuro D, Ries M, Chettipally U, Kerem Y, Jay M, Mataraso S, Das R.

J Med Econ. 2017 Jun;20(6):646-651. doi: 10.1080/13696998.2017.1307203. Epub 2017 Apr 3.

PMID:
28294646
13.

Using electronic health record collected clinical variables to predict medical intensive care unit mortality.

Calvert J, Mao Q, Hoffman JL, Jay M, Desautels T, Mohamadlou H, Chettipally U, Das R.

Ann Med Surg (Lond). 2016 Sep 6;11:52-57. eCollection 2016 Nov.

14.

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 MD, Barton C, Wales DJ, Das R.

JMIR Med Inform. 2016 Sep 30;4(3):e28.

15.

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.

Ann Med Surg (Lond). 2016 May 10;8:50-5. doi: 10.1016/j.amsu.2016.04.023. eCollection 2016 Jun.

16.

Energy landscapes for a machine-learning prediction of patient discharge.

Das R, Wales DJ.

Phys Rev E. 2016 Jun;93(6):063310. doi: 10.1103/PhysRevE.93.063310. Epub 2016 Jun 17.

PMID:
27415390
17.

A computational approach to mortality prediction of alcohol use disorder inpatients.

Calvert J, Mao Q, Rogers AJ, Barton C, Jay M, Desautels T, Mohamadlou H, Jan J, Das R.

Comput Biol Med. 2016 Aug 1;75:74-9. doi: 10.1016/j.compbiomed.2016.05.015. Epub 2016 May 24.

PMID:
27253619
18.

A computational approach to early sepsis detection.

Calvert JS, Price DA, Chettipally UK, Barton CW, Feldman MD, Hoffman JL, Jay M, Das R.

Comput Biol Med. 2016 Jul 1;74:69-73. doi: 10.1016/j.compbiomed.2016.05.003. Epub 2016 May 12.

PMID:
27208704
19.

Energy landscapes for a machine learning application to series data.

Ballard AJ, Stevenson JD, Das R, Wales DJ.

J Chem Phys. 2016 Mar 28;144(12):124119. doi: 10.1063/1.4944672.

PMID:
27036439
20.

Discharge recommendation based on a novel technique of homeostatic analysis.

Calvert JS, Price DA, Barton CW, Chettipally UK, Das R.

J Am Med Inform Assoc. 2017 Jan;24(1):24-29. doi: 10.1093/jamia/ocw014. Epub 2016 Mar 28.

PMID:
27026611

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