E-LIB Suche - Ergebnisse für: Baron, Jason M

1

Use of machine learning to predict clinical decision suppor..:

Baron, Jason M ; Huang, Richard ; McEvoy, Dustin.
JAMIA Open. 4 (2021) 1 - p. , 2021

Link: https://doi.org/10.1093/..

2

Real evidence to assess clinical testing interference risk ..:

Baron, Jason M. ; Heaney, Denise L. ; John, Ani.
Clinica Chimica Acta. 523 (2021) - p. 178-184 , 2021

Link: https://doi.org/10.1016/..

3

Development of a "meta-model" to address missing data, pred..:

Baron, Jason M ; Paranjape, Ketan ; Love, Tara...
Journal of the American Medical Informatics Association. 28 (2020) 3 - p. 605-615 , 2020

Link: https://doi.org/10.1093/..

4

Iron studies and transferrin, a source of test ordering con..:

Huang, Richard ; McEvoy, Dustin S. ; Baron, Jason M..
Clinica Chimica Acta. 510 (2020) - p. 337-343 , 2020

Link: https://doi.org/10.1016/..

5

Validation and Implementation of an Ordering Alert to Impro..:

Uljon, Sacha N ; Simmons, Daimon P ; Rudolf, Joseph W...
American Journal of Clinical Pathology. 153 (2019) 3 - p. 396-406 , 2019

Link: https://doi.org/10.1093/..

6

Order Indication Solicitation to Assess Clinical Laboratory..:

Rudolf, Joseph W. ; Baron, Jason M. ; Dighe, Anand S.
Journal of Pathology Informatics. 10 (2019) 1 - p. 36 , 2019

Link: https://doi.org/10.4103/..

7

Machine Learning Models Improve the Diagnostic Yield of Per..:

Zhang, M Lisa ; Guo, Alan X ; Kadauke, Stephan...
American Journal of Clinical Pathology. 153 (2019) 2 - p. 235-242 , 2019

Link: https://doi.org/10.1093/..

8

Using Machine Learning-Based Multianalyte Delta Checks to D..:

Rosenbaum, Matthew W ; Baron, Jason M
American Journal of Clinical Pathology. 150 (2018) 6 - p. 555-566 , 2018

Link: https://doi.org/10.1093/..

9

3D-MICE: integration of cross-sectional and longitudinal im..:

Luo, Yuan ; Szolovits, Peter ; Dighe, Anand S.
Journal of the American Medical Informatics Association. 25 (2017) 6 - p. 645-653 , 2017

Link: https://doi.org/10.1093/..

10

Analysis of Daily Laboratory Orders at a Large Urban Academ..:

Rudolf, Joseph W. ; Dighe, Anand S. ; Coley, Christopher M....
American Journal of Clinical Pathology. 148 (2017) 2 - p. 128-135 , 2017

Link: https://doi.org/10.1093/..

11

Using Machine Learning to Predict Laboratory Test Results:

Luo, Yuan ; Szolovits, Peter ; Dighe, Anand S.
American Journal of Clinical Pathology. 145 (2016) 6 - p. 778-788 , 2016

Link: https://doi.org/10.1093/..

12

Perceptions of pathology informatics by non-informaticist p..:

Walker, Addie ; Garcia, Christopher ; Baron, Jason M....
Journal of Pathology Informatics. 7 (2016) 1 - p. 14 , 2016

Link: https://doi.org/10.4103/..

13

ST2 Predicts Mortality and Length of Stay in a Critically I..:

Rudolf, Joseph W. ; Lewandrowski, Elizabeth L. ; Lewandrowski, Kent B....
American Journal of Clinical Pathology. 145 (2016) 2 - p. 203-210 , 2016

Link: https://doi.org/10.1093/..

14

Applying Lean methodologies reduces ED laboratory turnaroun..:

White, Benjamin A. ; Baron, Jason M. ; Dighe, Anand S...
The American Journal of Emergency Medicine. 33 (2015) 11 - p. 1572-1576 , 2015

Link: https://doi.org/10.1016/..

15

Clinical laboratory analytics: Challenges and promise for a..:

Shirts, Brian H. ; Jackson, Brian R. ; Baird, Geoffrey S....
Journal of Pathology Informatics. 6 (2015) 1 - p. 9 , 2015

Link: https://doi.org/10.4103/..