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Cited by 128Machine Learning in HealthcareArtificial Intelligence in Healthcare and EducationComputational Drug Discovery Methods

The DOI matches its Crossref record; 142 of the 146 references it cites were found in a registry or an index.

Learning for Personalized Medicine: A Comprehensive Review From a Deep Learning Perspective

Zhang, Sushen, Bamakan, Seyed Mojtaba Hosseini, Qu, Qiang, Li, Sha·2019·IEEE Reviews in Biomedical Engineering
DOI 10.1109/rbme.2018.2864254
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Abstract

With the recent advancements in analyzing high-volume, complex, and unstructured data, modern learning methods are playing an increasingly critical role in the field of personalized medicine. Personalized medicine (i.e., providing tailored medical treatment to individual patients through the identification of common features, including their genetics, inheritance, and lifestyle) has attracted the attention of many researchers in recent years. This paper provides an overview of the research progress in the application of learning methods, with a focus on deep learning in personalized medicine. In particular, three domains of applications are reviewed: drug development, disease characteristic identification, and therapeutic effect prediction. The main objective of this review is to consider the applied methods in detail and to offer insights into their pros and cons. Although having demonstrated advantages in coping with data complexity and nonlinearity and in recognizing features and associating structural data, the studied learning methods are not a panacea to all medical problems. Hence, we discuss the existing research challenges and clarify future study directions.

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Research works printed but not linked: 4

  1. davis, 0, Machine learning for personalized medicine: Will this drug give me a heart attack, Proc Int Conf Mach Learn
  2. 10.1016/0364-0213(90)90002-E · DOI · Paper page
  3. 10.1001/jama.1975.03260250028021 · DOI
  4. goodfellow, 2016, Deep Learning, 1

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Metadata

Authors
Zhang, S., Bamakan, S. M. H., Qu, Q., & Li, S.
Affiliations
Chinese Academy of Sciences (CN)
ORCID
Venue
IEEE Reviews in Biomedical Engineering
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2019
Volume
12
Pages
194-208
ISSN
  • 1937-3333 (ISSN-L)
  • 1941-1189
DOI
10.1109/rbme.2018.2864254
OpenAlex
W2887975519
Cited by
125
References
146
Citations by year
2026: 7 · 2025: 21 · 2024: 30 · 2023: 20 · 2022: 19 · 2021: 17 · 2020: 9 · 2019: 2
FWCI
0.81
Type
journal article
Language
en
Open access
closed
Licence
Locations
  • IEEE Reviews in Biomedical Engineering (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • CAS Pioneer Hundred Talents Program, China (Y84402, 2017)
  • China Postdoctoral Science Foundation (2018M633186, 2018)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Keywords
personalized medicine, deep learning, drug development, genetic data, machine learning in medicine
MeSH terms
Drug Development, Deep Learning, Humans, Research, Precision Medicine

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