Mohammad T. Khasawneh
Mohammad T. Khasawneh
SUNY Distinguished Professor, Systems Science & Industrial Engineering, Binghamton University (SUNY)
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Cited by
Cited by
A logistic approximation to the cumulative normal distribution
SR Bowling, MT Khasawneh, S Kaewkuekool, BR Cho
Journal of industrial engineering and management 2 (1), 114-127, 2009
Lead‐time reduction utilizing lean tools applied to healthcare: The inpatient pharmacy at a local hospital
O Al‐Araidah, A Momani, M Khasawneh, M Momani
Journal for Healthcare Quality 32 (1), 59-66, 2010
Predictive modeling of hospital readmissions using metaheuristics and data mining
B Zheng, J Zhang, SW Yoon, SS Lam, M Khasawneh, S Poranki
Expert Systems with Applications 42 (20), 7110-7120, 2015
A Markovian approach to determining optimum process target levels for a multi-stage serial production system
SR Bowling, MT Khasawneh, S Kaewkuekool, BR Cho
European Journal of Operational Research 159 (3), 636-650, 2004
A systematic review of research design and modeling techniques in inpatient bed management
L He, SC Madathil, A Oberoi, G Servis, MT Khasawneh
Computers & Industrial Engineering 127, 451-466, 2019
Advancing evidence-based healthcare facility design: a systematic literature review
F Halawa, SC Madathil, A Gittler, MT Khasawneh
Health Care Management Science 23, 453-480, 2020
Entropy generation due to laminar forced convection in the entrance region of a concentric annulus
OM Haddad, MK Alkam, MT Khasawneh
Energy 29 (1), 35-55, 2004
A new hybrid approach for feature selection and support vector machine model selection based on self-adaptive cohort intelligence
M Aladeemy, S Tutun, MT Khasawneh
Expert Systems with Applications 88, 118-131, 2017
Application of Lean Six Sigma tools to minimise length of stay for ophthalmology day case surgery
N Mandahawi, O Al-Araidah, A Boran, M Khasawneh
International Journal of Six Sigma and Competitive Advantage 6 (3), 156-172, 2011
New feature selection methods based on opposition-based learning and self-adaptive cohort intelligence for predicting patient no-shows
M Aladeemy, L Adwan, A Booth, MT Khasawneh, S Poranki
Applied Soft Computing 86, 105866, 2020
New framework that uses patterns and relations to understand terrorist behaviors
S Tutun, MT Khasawneh, J Zhuang
Expert Systems with Applications 78, 358-375, 2017
An overbooking scheduling model for outpatient appointments in a multi-provider clinic
B Zheng, SW Yoon, MT Khasawneh
Operations Research for Health Care 6, 1-10, 2015
Evaluation of alternate multimedia for web-based asynchronous learning
A Bhowmick, MT Khasawneh, SR Bowling, AK Gramopadhye, BJ Melloy
International Journal of Industrial Ergonomics 37 (7), 615-629, 2007
An analysis of overlapping appointment scheduling model in an outpatient clinic
K Anderson, B Zheng, SW Yoon, MT Khasawneh
Operations Research for Health Care 4, 5-14, 2015
Measurement of human trust in a hybrid inspection system based on signal detection theory measures
X Jiang, MT Khasawneh, R Master, SR Bowling, AK Gramopadhye, ...
International journal of industrial ergonomics 34 (5), 407-419, 2004
Tables of a truncated standard normal distribution: a doubly truncated case
MT Khasawneh, SR Bowling, S Kaewkuekool, BR Cho
Quality Engineering 17 (2), 227-241, 2005
Measurement of trust over time in hybrid inspection systems
R Master, X Jiang, MT Khasawneh, SR Bowling, L Grimes, ...
Human Factors and Ergonomics in Manufacturing & Service Industries 15 (2 …, 2005
Evaluating the effects of virtual training in an aircraft maintenance task
SR Bowling, MT Khasawneh, S Kaewkuekool, X Jiang, AK Gramopadhye
The International Journal of Aviation Psychology 18 (1), 104-116, 2008
A model for predicting human trust in automated systems
MT Khasawneh, SR Bowling, X Jiang, AK Gramopadhye, BJ Melloy
Origins 5, 216-222, 2003
G-Forest: An ensemble method for cost-sensitive feature selection in gene expression microarrays
M Abdulla, MT Khasawneh
Artificial Intelligence in Medicine 108, 101941, 2020
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