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Journal Photo for Health and Technology
Peer reviewed only Open Access

Health and Technology (H&T)

Publisher : IUPESM and Springer-Verlag
Biochemistry Genetics Chemical Engineering
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e-ISSN 2190-7196
p-ISSN 2190-7188
Issue Frequency Quarterly
Impact Factor 3.1
Est. Year 2011
Mobile 4962213450
DOI YES
Language English
APC YES
Impact Factor Assignee Google Scholar
Email customerservice@springernature.com

Journal Descriptions

Health and Technology is a cross-disciplinary journal addressing health, care, and health technology professions. First of its kind to cater to professional groups involved in health technologies. Encourages medical and scientific research professionals to write for a diverse readership. Official Journal of the IUPSEM (International Union for Physical and Engineering Sciences in Medicine), jointly published by Springer and the IUPESM, in cooperation with the World Health Organization. Follows a stringent double-blind reviewing procedure. Presents and discusses subjects including patient safety, disease management, e-health, data security, and health technology assessment. The journal achieved its inaugural impact factor of 2.5 in 2022.

Health and Technology (H&T) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Biochemistry, Genetics, Chemical Engineering, Applied Microbiology, Biotechnology , Online or Print , Quarterly Journal

  • UGC Approved, ISSN Approved: P-ISSN P-ISSN: 2190-7188, E-ISSN: 2190-7196, Established: 2011, Impact Factor: 3.1
  • Provides Crossref DOI

  • Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Publications of H&T

Real time health care big data analytics model for improved QoS in cardiac disease prediction with IoT devices
Gururaj H L June, 2023
Purpose the problem of big data analytics and health care support systems are analyzed. There exist several techniques in supporting such analytics and robust support systems; still, they s...
A comparative evaluation of machine learning ensemble approaches for disease prediction using multiple datasets
Mohammad Ali Moni March, 2024
Purpose Machine learning models are used to develop and improve various disease prediction systems. Ensemble learning is a machine learning technique that combines many classifiers to incre...