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Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto-ML
- Source :
- International journal of laboratory hematologyREFERENCES. 43
- Publication Year :
- 2021
-
Abstract
- Artificial Intelligence (AI) and machine learning (ML) have now spawned a new field within health care and health science research. These new predictive analytics tools are starting to change various facets of our clinical care domains including the practice of laboratory medicine. Many of these ML tools and studies are also starting to populate our literature landscape as we know it but unfamiliarity of the average reader to the basic knowledge and critical concepts within AI/ML is now demanding a need to better prepare our audience to such relatively unfamiliar concepts. A fundamental knowledge of such platforms will inevitably enhance cross-disciplinary literacy and ultimately lead to enhanced integration and understanding of such tools within our discipline. In this review, we provide a general outline of AI/ML along with an overview of the fundamental concepts of ML categories, specifically supervised, unsupervised, and reinforcement learning. Additionally, since the vast majority of our current approaches within ML in laboratory medicine and health care involve supervised algorithms, we will predominantly concentrate on such platforms. Finally, the need for making such tools more accessible to the average investigator is becoming a major driving force for the need of automation within these ML platforms. This has now given rise to the automated ML (Auto-ML) world which will undoubtedly help shape the future of ML within health care. Hence, an overview of Auto-ML is also covered within this manuscript which will hopefully enrich the reader's understanding, appreciation, and the need for embracing such tools.
- Subjects :
- Computer science
media_common.quotation_subject
Clinical Biochemistry
Medical laboratory
Machine learning
computer.software_genre
Field (computer science)
Literacy
Workflow
Machine Learning
Automation
Artificial Intelligence
Health care
Medical Laboratory Science
Reinforcement learning
media_common
business.industry
Biochemistry (medical)
Supervised learning
Hematology
General Medicine
Predictive analytics
Research Design
Artificial intelligence
Supervised Machine Learning
business
computer
Delivery of Health Care
Algorithms
Subjects
Details
- ISSN :
- 1751553X
- Volume :
- 43
- Database :
- OpenAIRE
- Journal :
- International journal of laboratory hematologyREFERENCES
- Accession number :
- edsair.doi.dedup.....088317452e9f47ac104caca752378f09