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International Journal of Biomedical Data Mining

International Journal of Biomedical Data Mining
Open Access

ISSN: 2090-4924

International Journal of Biomedical Data Mining : Citations & Metrics Report

Articles published in International Journal of Biomedical Data Mining have been cited by esteemed scholars and scientists all around the world. International Journal of Biomedical Data Mining has got h-index 7, which means every article in International Journal of Biomedical Data Mining has got 7 average citations.

Following are the list of articles that have cited the articles published in International Journal of Biomedical Data Mining.

  2020 2019 2018 2017 2016

Year wise published articles

33 2 4 8 5

Year wise citations received

42 62 70 46 14
Journal total citations count 310
Journal impact factor 6.83
Journal 5 years impact factor 4.42
Journal cite score 4.60
Journal h-index 7
Journal h-index since 2017 7
Important citations

Study of the cytotoxic effects of aflatoxin on hematopoietic stem cells

A study to evaluate aflatoxin contamination in food from gauteng province

Aflatoxins in the soil ecosystem: an overview of its occurrence, fate, effects and future perspectives

Fungi and aflatoxin occurrence in fresh and dried vegetables marketed in minna, niger state, nigeria

A focus on aflatoxins in feedstuffs: levels of contamination, prevalence, control strategies, and impacts on animal health

Comparative genomics a new arena of biological research: a review

An engineering approach to bioinformatics and its applications

Bioinformatics: how it helps to boost modern biological research

A bioinformatic pipeline for monitoring of the mutational stability of viral drug targets with deep-sequencing technology

Computational analysis of next generation sequencing data and its applications in clinical oncology

An overview of data mining techniques to support medical decisions

Performance analysis of predicting survival rates in imbalanced healthcare dataset.

Machine learning with applications

Edge-based convolutional neural network for improving breast cancer prediction performance

Ensemble based filter feature selection with harmonize particle swarm optimization and support vector machine for optimal cancer classification

Mendelian randomization study of the association between telomere length and risk of cancer and non-neoplastic disease

Relevant Topics