|Reference ranges for hematocrit and blood hemoglobin concentration during the neonatal period: data from a multihospital health care system|
J Jopling, E Henry, SE Wiedmeier, RD Christensen
Pediatrics 123 (2), e333-e337, 2009
|The CBC: reference ranges for neonates|
RD Christensen, E Henry, J Jopling, SE Wiedmeier
Seminars in perinatology 33 (1), 3-11, 2009
|Expected ranges for blood neutrophil concentrations of neonates: the Manroe and Mouzinho charts revisited|
N Schmutz, E Henry, J Jopling, RD Christensen
Journal of Perinatology 28 (4), 275, 2008
|The erythrocyte indices of neonates, defined using data from over 12 000 patients in a multihospital health care system|
RD Christensen, J Jopling, E Henry, SE Wiedmeier
Journal of Perinatology 28 (1), 24, 2008
|Tool detection and operative skill assessment in surgical videos using region-based convolutional neural networks|
A Jin, S Yeung, J Jopling, J Krause, D Azagury, A Milstein, L Fei-Fei
2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 691-699, 2018
|Identifying Distinct Subgroups of Intensive Care Unit Patients: a Machine Learning Approach|
KC Vranas, JK Jopling, TE Sweeney, MC Ramsey, AS Milstein, ...
Critical care medicine 45 (10), 1607, 2017
|Towards vision-based smart hospitals: A system for tracking and monitoring hand hygiene compliance|
A Haque, M Guo, A Alahi, S Yeung, Z Luo, A Rege, J Jopling, L Downing, ...
arXiv preprint arXiv:1708.00163, 2017
|Priority queuing models for hospital intensive care units and impacts to severe case patients|
MS Hagen, JK Jopling, TG Buchman, EK Lee
AMIA Annual Symposium Proceedings 2013, 841, 2013
|Sepsis through the Eyes of an Engineer− Why Treatments Have Succeeded and Failed|
J Jopling, TG Buchman
Critical Reviews™ in Biomedical Engineering 40 (4), 2012
|To cut is to cure: the surgeon's role in improving value|
JK Jopling, CC Sheckter, BC James
Annals of surgery 267 (5), 817-819, 2018
|A computer vision system for deep learning-based detection of patient mobilization activities in the ICU|
S Yeung, F Rinaldo, J Jopling, B Liu, R Mehra, NL Downing, M Guo, ...
|Déjà Vu: Introducing Operations Research to Health Care|
TH Wagner, JK Jopling
Medical Decision Making 37 (8), 847-848, 2017
|Detecting organisational innovations leading to improved ICU outcomes: a protocol for a double-blinded national positive deviance study of critical care delivery|
H Chiou, JK Jopling, JY Scott, M Ramsey, K Vranas, TH Wagner, ...
BMJ open 7 (6), e015930, 2017
|BURNED: Towards Efficient and Accurate Burn Prognosis Using Deep Learning|
O Despo, S Yeung, J Jopling, B Pridgen, C Sheckter, S Silberstein, ...
|3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities|
B Liu, M Guo, E Chou, R Mehra, S Yeung, NL Downing, F Salipur, ...
Machine Learning for Healthcare Conference, 17-29, 2018
|Vision-Based Prediction of ICU Mobility Care Activities using Recurrent Neural Networks|
G Bianconi, R Mehra, S Yeung, F Salipur, J Jopling, L Downing, A Haque, ...
NIPS workshop on Machine Learning for Health, 2017
|Estimating The Proportion Of Patients" too Well" To Benefit From Critical Care: A Machine Learning Approach|
K Vranas, J Jopling, M Ramsey, TE Sweeney, GJ Escobar, V Liu
B46. CRITICAL CARE: ICU EPIDEMIOLOGY AND OUTCOMES, A3632-A3632, 2016
|Performance improvement in surgery.|
RF Alban, EC Anania, TN Cohen, PJ Fabri, BL Gewertz, M Jain, ...
Current problems in surgery 56 (6), 204-208, 2019
|Resident-Sensitive Processes of Care: Impact of Surgical Residents on Inpatient Testing|
CC Sheckter, J Jopling, Q Ding, AW Trickey, T Wagner, AM Morris, ...
Journal of the American College of Surgeons 228 (5), 798-806. e2, 2019
|33 Automated Burn Assessment using Deep Learning and Computer Vision|
BC Pridgen, JK Jopling, CC Sheckter, O Despo, S Yeung, Y Karanas, F Li, ...
Journal of Burn Care & Research 40 (Supplement_1), S25-S26, 2019