Journal article
Review of Medical Decision Support and Machine-Learning Methods
Veterinary pathology, Vol.56(4), pp.512-525
07/01/2019
DOI: 10.1177/0300985819829524
PMID: 30866728
Abstract
Machine-learning methods can assist with the medical decision-making processes at the both the clinical and diagnostic levels. In this article, we first review historical milestones and specific applications of computer-based medical decision support tools in both veterinary and human medicine. Next, we take a mechanistic look at 3 archetypal learning algorithms-naive Bayes, decision trees, and neural network-commonly used to power these medical decision support tools. Last, we focus our discussion on the data sets used to train these algorithms and examine methods for validation, data representation, transformation, and feature selection. From this review, the reader should gain some appreciation for how these decision support tools have and can be used in medicine along with insight on their inner workings.
Details
- Title: Subtitle
- Review of Medical Decision Support and Machine-Learning Methods
- Creators
- Abdullah Awaysheh - Virginia–Maryland College of Veterinary MedicineJeffrey Wilcke - Virginia–Maryland College of Veterinary MedicineFrancois Elvinger - Virginia TechLoren Rees - Pamplin College of BusinessWeiguo Fan - Pamplin College of BusinessKurt L. Zimmerman - Virginia–Maryland College of Veterinary Medicine
- Resource Type
- Journal article
- Publication Details
- Veterinary pathology, Vol.56(4), pp.512-525
- Publisher
- Sage
- DOI
- 10.1177/0300985819829524
- PMID
- 30866728
- ISSN
- 0300-9858
- eISSN
- 1544-2217
- Number of pages
- 14
- Language
- English
- Date published
- 07/01/2019
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380458002771
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