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Alan L. Chang

Stanford University - Department of Anesthesiology

SCHOLARLY PAPERS

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Scholarly Papers (2)

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1.

Comprehensive Overview of the Anesthesiology Research Landscape: A Machine Learning Analysis of 737 Nih-Funded Anesthesiology Primary Investigator's Publication Trends

Number of pages: 42 Posted: 03 Jan 2024
Marc Ghanem, Camilo Espinosa, Philip Chung, Momsen Reincke, Natasha Harrison, Thanaphong Phongpreecha, Sayane Shome, Geetha Saarunya, Eloise Berson, Tomin James, Feng Xie, Chi-Hung Shu, Debapriya Hazra, Samson Mataraso, Yeasul Kim, David Seong, Dipro Chakraborty, Manuel Studer, Lei Xue, Ivana Marić, Alan L. Chang, Erico Tjoa, Brice Gaudilliere, Vivianne L. Tawfik, Sean Mackey and Nima Aghaeepour
Stanford University, Stanford University - Department of Anesthesiology, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Dascena, Inc.,, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University, Stanford University - Department of Pediatrics, Stanford University - Department of Anesthesiology, Stanford University, Stanford University - Department of Pediatrics, Stanford University - Department of Anesthesiology, Perioperative & Pain Medicine, Stanford University - Division of Pain Medicine and Stanford University - Department of Pediatrics
Downloads 102 (684,672)

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Anesthesiology research trendsTopic modelingPillar topicsTrending subtopicsNIH-funded researchArtificial intelligenceMachine Learning

2.

Early Prediction and Longitudinal Modeling of Preeclampsia from Multiomics

Number of pages: 80 Posted: 16 Jun 2022
Ivana Marić, Kévin Contrepois, Mira N. Moufarrej, Ina A. Stelzer, Dorien Feyaerts, Xiaoyuan Han, Andy Tang, Natalie Stanley, Ronald J. Wong, Gavin M. Traber, Mathew Ellenberger, Alan L. Chang, Ramin Fallahzadeh, Huda Nassar, Martin Becker, Maria Xenochristou, Camilo Espinosa, Davide De Francesco, Mohammad S. Ghaemi, Elizabeth K. Costello, tony culos, Xuefeng B. Ling, Karl G. Sylvester, Gary L. Darmstadt, Virginia D. Winn, Gary M. Shaw, David Relman, Stephen R. Quake, Martin S. Angst, Michael Snyder, David K. Stevenson, Brice Gaudilliere and Nima Aghaeepour
Stanford University - Department of Pediatrics, Stanford University - Genetics Department, Stanford University - Departments of Bioengineering and Applied Physics, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, University of the Pacific (UOP) - Arthur Dugoni School of Dentistry, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Pediatrics, Stanford University - Genetics Department, Stanford University - Genetics Department, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Anesthesiology, Stanford University - Department of Medicine, Stanford University - Department of Anesthesiology, Stanford University - Clinical and Translational Research Program, affiliation not provided to SSRN, Stanford University - Department of Pediatrics, Stanford University - Department of Obstetrics and Gynecology, Stanford University - Department of Pediatrics, Stanford University - Institute for Immunity, Transplantation, and Infection, Stanford University - Department of Bioengineering, Stanford University - Department of Anesthesiology, Stanford University - Genetics Department, Stanford University - Department of Pediatrics, Stanford University - Department of Pediatrics and Stanford University - Department of Pediatrics
Downloads 35 (1,249,711)

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preeclampsia, machine learning, predictive modelling, multiomics, biomarkers.