Literature DB >> 33608148

Bridging the artificial intelligence valley of death in surgical decision-making.

Jeremy Balch1, Gilbert R Upchurch2, Azra Bihorac3, Tyler J Loftus4.   

Abstract

Entities:  

Mesh：

Year:  2021        PMID： 33608148      PMCID： PMC8276528          DOI： 10.1016/j.surg.2021.01.008

Source DB:  PubMed          Journal:  Surgery        ISSN： 0039-6060            Impact factor:   3.982


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  13 in total

1.  Medicine and the computer. The promise and problems of change.

Authors:  W B Schwartz
Journal:  N Engl J Med       Date:  1970-12-03       Impact factor: 91.245

2.  Leveraging interpretable machine learning algorithms to predict postoperative patient outcomes on mobile devices.

Authors:  Majed W El Hechi; Samer A Nour Eddine; Lydia R Maurer; Haytham M A Kaafarani
Journal:  Surgery       Date:  2020-09-09       Impact factor: 3.982

3.  Machine Learning, Predictive Analytics, and Clinical Practice: Can the Past Inform the Present?

Authors:  Eric D Peterson
Journal:  JAMA       Date:  2019-12-17       Impact factor: 56.272

4.  Estimate the hidden deployment cost of predictive models to improve patient care.

Authors:  Keith E Morse; Steven C Bagley; Nigam H Shah
Journal:  Nat Med       Date:  2020-01       Impact factor: 53.440

5.  Machine learning in intensive care medicine: ready for take-off?

Authors:  Lucas M Fleuren; Patrick Thoral; Duncan Shillan; Ari Ercole; Paul W G Elbers
Journal:  Intensive Care Med       Date:  2020-05-12       Impact factor: 17.440

6.  Adverse Events After Transition From ICU to Hospital Ward: A Multicenter Cohort Study.

Authors:  Khara M Sauro; Andrea Soo; Chloe de Grood; Michael M H Yang; Benjamin Wierstra; Luc Benoit; Philippe Couillard; François Lamontagne; Alexis F Turgeon; Alan J Forster; Robert A Fowler; Peter M Dodek; Sean M Bagshaw; Henry T Stelfox
Journal:  Crit Care Med       Date:  2020-07       Impact factor: 7.598

Review 7.  One of the first validations of an artificial intelligence algorithm for clinical use: The impact on intraoperative hypotension prediction and clinical decision-making.

Authors:  Ward H van der Ven; Denise P Veelo; Marije Wijnberge; Björn J P van der Ster; Alexander P J Vlaar; Bart F Geerts
Journal:  Surgery       Date:  2020-12-11       Impact factor: 3.982

8.  Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial.

Authors:  Marije Wijnberge; Bart F Geerts; Liselotte Hol; Nikki Lemmers; Marijn P Mulder; Patrick Berge; Jimmy Schenk; Lotte E Terwindt; Markus W Hollmann; Alexander P Vlaar; Denise P Veelo
Journal:  JAMA       Date:  2020-03-17       Impact factor: 56.272

9.  MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery.

Authors:  Azra Bihorac; Tezcan Ozrazgat-Baslanti; Ashkan Ebadi; Amir Motaei; Mohcine Madkour; Panagote M Pardalos; Gloria Lipori; William R Hogan; Philip A Efron; Frederick Moore; Lyle L Moldawer; Daisy Zhe Wang; Charles E Hobson; Parisa Rashidi; Xiaolin Li; Petar Momcilovic
Journal:  Ann Surg       Date:  2019-04       Impact factor: 12.969

10.  Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension.

Authors:  Shounak Datta; Tyler J Loftus; Matthew M Ruppert; Chris Giordano; Gilbert R Upchurch; Parisa Rashidi; Tezcan Ozrazgat-Baslanti; Azra Bihorac
Journal:  J Surg Res       Date:  2020-06-09       Impact factor: 2.192
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