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Paper Details

Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome.
PLoS One
5
2022
human, hypertension, patient, rare, spinal cord injury
Artificial Intelligence, Hemodynamics, Humans, Machine Learning, Reproducibility of Results, Spinal Cord Injuries
Author NameAffiliation
Austin ChouWeill Institute for Neurosciences, University of California san francisco
Austin ChouZuckerberg San Francisco General Hospital and Trauma Center
Austin ChouUniversity of California san francisco
Austin ChouWeill Institute for Neurosciences, University of California san francisco
Austin ChouUniversity of California san francisco
Austin ChouZuckerberg San Francisco General Hospital and Trauma Center
Abel Torres-EspinWeill Institute for Neurosciences, University of California san francisco
Abel Torres-EspinZuckerberg San Francisco General Hospital and Trauma Center
Abel Torres-EspinUniversity of California san francisco
Abel Torres-EspinWeill Institute for Neurosciences, University of California san francisco
Abel Torres-EspinUniversity of California san francisco
Abel Torres-EspinZuckerberg San Francisco General Hospital and Trauma Center
Nikos KyritsisWeill Institute for Neurosciences, University of California san francisco
Nikos KyritsisUniversity of California san francisco
Nikos KyritsisZuckerberg San Francisco General Hospital and Trauma Center
John R HuieWeill Institute for Neurosciences, University of California san francisco
John R HuieZuckerberg San Francisco General Hospital and Trauma Center
John R HuieUniversity of California san francisco
John R HuieWeill Institute for Neurosciences, University of California san francisco
John R HuieUniversity of California san francisco
John R HuieZuckerberg San Francisco General Hospital and Trauma Center
Sarah KhatryInc.
Jeremy FunkInc.
Jennifer HayInc.
Andrew LofgreenInc.
Rajiv ShahInc.
Chandler McCannInc.
Lisa U PascualOrthopedic Trauma Institute, University of California san francisco
Edilberto AmorimZuckerberg San Francisco General Hospital and Trauma Center
Edilberto AmorimUniversity of California san francisco
Philip R WeinsteinUniversity of California san francisco
Philip R WeinsteinUniversity of California san francisco
Philip R WeinsteinWeill Institute for Neurosciences, Institute for Neurodegenerative Diseases, University of California san francisco
Geoffrey T ManleyWeill Institute for Neurosciences, University of California san francisco
Geoffrey T ManleyZuckerberg San Francisco General Hospital and Trauma Center
Geoffrey T ManleyUniversity of California san francisco
Geoffrey T ManleyWeill Institute for Neurosciences, University of California san francisco
Geoffrey T ManleyUniversity of California san francisco
Geoffrey T ManleyZuckerberg San Francisco General Hospital and Trauma Center
Sanjay S DhallWeill Institute for Neurosciences, University of California san francisco
Sanjay S DhallUniversity of California san francisco
Sanjay S DhallZuckerberg San Francisco General Hospital and Trauma Center
Jonathan Z PanWeill Institute for Neurosciences, University of California san francisco
Jonathan Z PanUniversity of California san francisco
Jacqueline C BresnahanWeill Institute for Neurosciences, University of California san francisco
Jacqueline C BresnahanZuckerberg San Francisco General Hospital and Trauma Center
Jacqueline C BresnahanUniversity of California san francisco
Jacqueline C BresnahanWeill Institute for Neurosciences, University of California san francisco
Jacqueline C BresnahanUniversity of California san francisco
Jacqueline C BresnahanZuckerberg San Francisco General Hospital and Trauma Center
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