Allen Zhang

ORCID: 0000-0001-9455-866X
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About
Contact & Profiles
Research Areas
  • Palliative Care and End-of-Life Issues
  • Health Systems, Economic Evaluations, Quality of Life
  • Intensive Care Unit Cognitive Disorders
  • Patient-Provider Communication in Healthcare
  • Patient Satisfaction in Healthcare
  • Obesity, Physical Activity, Diet
  • Suicide and Self-Harm Studies
  • Testicular diseases and treatments
  • Disaster Response and Management
  • Acute Kidney Injury Research
  • Pain Mechanisms and Treatments
  • Anesthesia and Sedative Agents
  • Botulinum Toxin and Related Neurological Disorders
  • Childhood Cancer Survivors' Quality of Life
  • Healthcare Policy and Management
  • Telemedicine and Telehealth Implementation
  • Anesthesia and Neurotoxicity Research
  • Patient Dignity and Privacy
  • Fiscal Policies and Political Economy
  • Obesity and Health Practices
  • Resilience and Mental Health
  • Sexual Differentiation and Disorders
  • Breastfeeding Practices and Influences
  • Infection Control in Healthcare
  • Housing Market and Economics

Johns Hopkins University
2016-2025

University of British Columbia
2024

University of Nevada, Las Vegas
2024

Tulane University
2018-2022

University of Hong Kong
2022

Johns Hopkins Medicine
2022

Agency for Healthcare Research and Quality
2019

Johns Hopkins Hospital
2017

Government of the United States of America
2017

Morehouse School of Medicine
2017

We analyze bidding data from uniform price auctions of US Treasury bills and notes between July 2009 October 2013. Primary dealers consistently bid higher yields compared to direct indirect bidders. estimate a structural model that takes into account informational asymmetries introduced by the system employed Treasury. While primary dealers' estimated willingness-to-pay is than bidders’, their ability bid-shade even higher, leading yield/lower bids. Total bidder surplus averaged about three...

10.1257/aer.20160675 article EN American Economic Review 2018-01-01

Abstract Investigation of histopathology slides by pathologists is an indispensable component the routine diagnosis cancer. Artificial intelligence (AI) has potential to enhance diagnostic accuracy, improve efficiency, and patient outcomes in clinical pathology. However, variations tissue preparation, staining protocols, slide digitization could result over-fitting deep learning models when trained on data from only one center, thereby underscoring necessity generalize networks for...

10.1038/s41698-024-00652-4 article EN cc-by npj Precision Oncology 2024-07-19

Abstract Ovarian cancer poses a significant health burden as one of the deadliest malignancies affecting women globally. Histotype assignment epithelial ovarian cancers can be challenging due to morphologic overlap, inter-observer variability, and lack ancillary diagnostic techniques in some areas world. Moreover, rare pose particular difficulties because relative familiarity with them, underscoring necessity for robust methodologies. The emergence Artificial Intelligence (AI) has brought...

10.1101/2024.04.19.24306099 preprint EN cc-by-nc-nd medRxiv (Cold Spring Harbor Laboratory) 2024-04-23
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