Abstract
Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few. Although, skepticism remains regarding the practical application and interpretation of results from ML-based approaches in healthcare settings, the inclusion of these approaches is increasing at a rapid pace. Here we provide a brief overview of machine learning-based approaches and learning algorithms including supervised, unsupervised, and reinforcement learning along with examples. Second, we discuss the application of ML in several healthcare fields, including radiology, genetics, electronic health records, and neuroimaging. We also briefly discuss the risks and challenges of ML application to healthcare such as system privacy and ethical concerns and provide suggestions for future applications.
Keywords: Machine learning, healthcare, support vector machine, EHR, genomics, artificial intelligence.
Current Genomics
Title:Machine Learning in Healthcare
Volume: 22 Issue: 4
Author(s): Hafsa Habehh and Suril Gohel*
Affiliation:
- Department of Health Informatics, Rutgers University School of Health Professions, 65 Bergen Street, Newark, NJ 07107,United States
Keywords: Machine learning, healthcare, support vector machine, EHR, genomics, artificial intelligence.
Abstract: Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few. Although, skepticism remains regarding the practical application and interpretation of results from ML-based approaches in healthcare settings, the inclusion of these approaches is increasing at a rapid pace. Here we provide a brief overview of machine learning-based approaches and learning algorithms including supervised, unsupervised, and reinforcement learning along with examples. Second, we discuss the application of ML in several healthcare fields, including radiology, genetics, electronic health records, and neuroimaging. We also briefly discuss the risks and challenges of ML application to healthcare such as system privacy and ethical concerns and provide suggestions for future applications.
Export Options
About this article
Cite this article as:
Habehh Hafsa and Gohel Suril*, Machine Learning in Healthcare, Current Genomics 2021; 22 (4) . https://dx.doi.org/10.2174/1389202922666210705124359
DOI https://dx.doi.org/10.2174/1389202922666210705124359 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
Call for Papers in Thematic Issues
Advanced AI Techniques in Big Genomic Data Analysis
The thematic issue on "Advanced AI Techniques in Big Genomic Data Analysis" aims to explore the cutting-edge methodologies and applications of artificial intelligence (AI) in the realm of genomic research, where vast amounts of data pose both challenges and opportunities. This issue will cover a broad spectrum of AI-driven strategies, ...read more
Advanced Computational Algorithms and Artificial Intelligence in Clinical Pharmacogenomics
In the era of personalized medicine, understanding the relationship between genetics and drug response is crucial. This issue delves into innovative methodologies, leveraging deep computational analysis and artificial intelligence, to enhance the field of Clinical Pharmacogenomics. The interdisciplinary approach harnesses the power of advanced high-throughput genotyping technologies, sophisticated computational analysis, ...read more
Applications of Single-cell Sequencing Technology in Reproductive Medicine
Single cell sequencing (SCS) technology utilizes individual cells' genetic material to sequence their genome, transcriptome, and epigenetics at the molecular level. It offers insights into cell heterogeneity and enables the study of limited biological materials. Since its recognition as a valuable technique in 2011, single cell sequencing has yielded numerous ...read more
Big Data in Cancer Research
Cancer is a significant threat to human life and health, remaining a highly aggressive killer. It is a leading cause of death worldwide and represents a crucial medical issue for humanity. However, in the past decade, the effectiveness of new synthetic anticancer agents has not matched the current clinical speculation. ...read more
Related Journals
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
Understanding the Molecular and Cellular Changes Behind Aortic Valve Stenosis
Current Pharmaceutical Biotechnology The Updated Role of the Blood Brain Barrier in Subarachnoid Hemorrhage: From Basic and Clinical Studies
Current Neuropharmacology Usefulness of Magnetic Resonance Imaging in Cardiac and Enovascular Intervention
Current Medical Imaging The Role of Renal Nerve Ablation for the Management of Resistant Hypertension and other Disease Conditions: Benefits and Concerns
Current Vascular Pharmacology Aldose Reductase Inhibition: Emerging Drug Target for the Treatment of Cardiovascular Complications
Recent Patents on Cardiovascular Drug Discovery Potential Roles of MyomiRs in Cardiac Development and Related Diseases
Current Cardiology Reviews Non-Steroidal Anti-Inflammatory Drugs used as a Treatment Modality in Subarachnoid Hemorrhage
Current Drug Safety COVID-19 in Children: A Narrative Review
Current Pediatric Reviews Cardiovascular Involvement in Pediatric Systemic Autoimmune Diseases: The Emerging Role of Noninvasive Cardiovascular Imaging
Inflammation & Allergy - Drug Targets (Discontinued) 3D Cell and Scaffold Patterning Strategies in Tissue Engineering
Recent Patents on Biomedical Engineering (Discontinued) An update on the Management and Treatment of Deep Vein Thrombosis
Cardiovascular & Hematological Agents in Medicinal Chemistry Template-Mediated Biomineralization for Bone Tissue Engineering
Current Stem Cell Research & Therapy Atrial Tachycardias Arising from the Atrial Appendages and Aortic Sinus of Valsalva
Current Cardiology Reviews COMPLICATIONS OF RECANALIZATION OF CHRONIC TOTAL OCCLUSION
Current Cardiology Reviews Hypoxia-Inducible Factor-1 in Arterial Disease: A Putative Therapeutic Target
Current Vascular Pharmacology New therapeutic effects of cilostazol in patients with ischemic disorders
Current Vascular Pharmacology Secondary Stroke Prevention in Patients with Cryptogenic Stroke and Patent Foramen Ovale
Vascular Disease Prevention (Discontinued) Virus-Associated Vasculitides: An Update
Current Immunology Reviews (Discontinued) Nanoparticles: A Promising Therapeutic Approach in Atherosclerosis
Current Drug Delivery Current Concepts on Cardiovascular Stent Devices
Mini-Reviews in Medicinal Chemistry