Machine Learning: Health
IOP Publishing · United Kingdom
Aims & Scope✦ Inferred from recent articles
This journal focuses on the application of artificial intelligence and machine learning techniques to various aspects of health and medicine. Key areas include medical image analysis, diagnostic support, physiological monitoring, and disease detection. The journal also addresses the development of tools and frameworks for improving the reliability, fairness, and efficiency of AI in healthcare settings.
AI-summarised from recent articles · verify on publisher page →
General Information
Submission Info
Ethics & Quality
Think.Check.Submit Compliance
A twelfth criterion — whether APC fees are clearly disclosed — is not scored here; it is left out of the total rather than counted as a failure. Publication charges appear in the metrics card above.
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
Subject Classification
Research Topics (OpenAlex)
Frequently asked questions about Machine Learning: Health
Is Machine Learning: Health a predatory journal?
PubScope has no integrity flags on record for Machine Learning: Health: it is indexed in DOAJ, and is not on DOAJ's withdrawn list. Indexing is a transparency signal, not a guarantee — always confirm fit and policies before submitting.
What is the impact factor of Machine Learning: Health?
Machine Learning: Health is not in the Web of Science Core Collection, so it has no official Clarivate Journal Impact Factor.
Is Machine Learning: Health indexed in Scopus and Web of Science?
Machine Learning: Health is indexed in DOAJ.
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See all →Data updated: 2026-05-26 · Sources: SJR, DOAJ, OpenAlex, WoS, Crossref