Literature DB >> 31932778

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

Keith E Morse1,2, Steven C Bagley3, Nigam H Shah3.   

Abstract

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Year:  2020        PMID： 31932778     DOI： 10.1038/s41591-019-0651-8

Source DB:  PubMed          Journal:  Nat Med        ISSN： 1078-8956            Impact factor:   53.440


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  10 in total

Review 1.  Artificial intelligence-enabled decision support in nephrology.

Authors:  Tyler J Loftus; Benjamin Shickel; Tezcan Ozrazgat-Baslanti; Yuanfang Ren; Benjamin S Glicksberg; Jie Cao; Karandeep Singh; Lili Chan; Girish N Nadkarni; Azra Bihorac
Journal:  Nat Rev Nephrol       Date:  2022-04-22       Impact factor: 42.439

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

Authors:  Jeremy Balch; Gilbert R Upchurch; Azra Bihorac; Tyler J Loftus
Journal:  Surgery       Date:  2021-02-16       Impact factor: 3.982

3.  A framework for making predictive models useful in practice.

Authors:  Kenneth Jung; Sehj Kashyap; Anand Avati; Stephanie Harman; Heather Shaw; Ron Li; Margaret Smith; Kenny Shum; Jacob Javitz; Yohan Vetteth; Tina Seto; Steven C Bagley; Nigam H Shah
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

4.  Development and utility assessment of a machine learning bloodstream infection classifier in pediatric patients receiving cancer treatments.

Authors:  Lillian Sung; Conor Corbin; Ethan Steinberg; Emily Vettese; Aaron Campigotto; Loreto Lecce; George A Tomlinson; Nigam Shah
Journal:  BMC Cancer       Date:  2020-11-13       Impact factor: 4.430

Review 5.  Economic evaluations of big data analytics for clinical decision-making: a scoping review.

Authors:  Lytske Bakker; Jos Aarts; Carin Uyl-de Groot; William Redekop
Journal:  J Am Med Inform Assoc       Date:  2020-07-01       Impact factor: 4.497

Review 6.  Deploying digital health tools within large, complex health systems: key considerations for adoption and implementation.

Authors:  Jayson S Marwaha; Adam B Landman; Gabriel A Brat; Todd Dunn; William J Gordon
Journal:  NPJ Digit Med       Date:  2022-01-27

7.  How can we discover the most valuable types of big data and artificial intelligence-based solutions? A methodology for the efficient development of the underlying analytics that improve care.

Authors:  Lytske Bakker; Jos Aarts; Carin Uyl-de Groot; Ken Redekop
Journal:  BMC Med Inform Decis Mak       Date:  2021-11-29       Impact factor: 2.796

8.  Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.

Authors:  Lin Lawrence Guo; Stephen R Pfohl; Jason Fries; Alistair E W Johnson; Jose Posada; Catherine Aftandilian; Nigam Shah; Lillian Sung
Journal:  Sci Rep       Date:  2022-02-17       Impact factor: 4.379

Review 9.  Clinical deployment environments: Five pillars of translational machine learning for health.

Authors:  Steve Harris; Tim Bonnici; Thomas Keen; Watjana Lilaonitkul; Mark J White; Nel Swanepoel
Journal:  Front Digit Health       Date:  2022-08-19

10.  Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study.

Authors:  Julian C Hong; Neville C W Eclov; Sarah J Stephens; Yvonne M Mowery; Manisha Palta
Journal:  BMC Bioinformatics       Date:  2022-09-30       Impact factor: 3.307
  10 in total

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