IRBM

Aims & Scope

IRBM is the journal of the AGBM (Alliance for engineering in Biology an Medicine / Alliance pour le génie biologique et médical) and the SFGBM (BioMedical Engineering French Society / Société française de génie biologique médical) and the AFIB (French Association of Biomedical Engineers / Association française des ingénieurs biomédicaux).

As a vehicle of information and knowledge in the field of biomedical technologies, IRBM is devoted to fundamental as well as clinical research.

Biomedical engineering and use of new technologies are the cornerstones of IRBM, providing authors and users with the latest information.

Its six issues per year propose reviews (state-of-the-art and current knowledge), original articles directed at fundamental research and articles focusing on biomedical engineering.

All articles are submitted to peer reviewers acting as guarantors for IRBM's scientific and medical content.

The field covered by IRBM includes all the discipline of Biomedical engineering.

Thereby, the type of papers published include those that cover the technological and methodological development in: -Physiological and Biological Signal processing (EEG, MEG, ECG…)- Medical Image processing- Biomechanics- Biomaterials- Medical Physics- Biophysics- Physiological and Biological Sensors- Information technologies in healthcare- Disability research- Computational physiology- …

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	4.2
2024	5.60

Journal Rank

Year	Value
2024	5694

Journal Citation Indicator

Year	Value
2024	1136

SJR (SCImago Journal Rank)

Year	Value
2024	0.900

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	48

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science
• Embase

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Biochemistry, Genetics and Molecular Biology and Engineering, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• TeleOphta: Machine learning and image processing methods for teleophthalmology

  Citation: 392

  Authors: E., G., X., G., J.-C., F., B., G., M., R., D., P., Z., A., B., A.

• A Hybrid CNN-SVM Threshold Segmentation Approach for Tumor Detection and Classification of MRI Brain Images

  Citation: 339

  Authors: M.O., M., V., J.M., N.Z.

• Deep Transfer Learning Based Classification Model for COVID-19 Disease

  Citation: 277

  Authors: Y., P.K., A., S., S., P.K.

• A proposal for the classification and evaluation of fall detectors

  Citation: 229

  Authors: N., P., A.K., G., J.E.

• A Deep Feature Learning Model for Pneumonia Detection Applying a Combination of mRMR Feature Selection and Machine Learning Models

  Citation: 227

  Authors: M., B., Z., F.

• A Review of the Deep Learning Methods for Medical Images Super Resolution Problems

  Citation: 223

  Authors: Y., B., F.

• A review of methods for non-invasive and continuous blood pressure monitoring: Pulse transit time method is promising?

  Citation: 213

  Authors: L., N., M.

• Deep Convolution Neural Network Based System for Early Diagnosis of Alzheimer's Disease

  Citation: 154

  Authors: R.R., Y.K.

• Automated Deep Transfer Learning-Based Approach for Detection of COVID-19 Infection in Chest X-rays

  Citation: 154

  Authors: N., N., M., V., D.

• Recent Trends in Computer Assisted Diagnosis (CAD) System for Breast Cancer Diagnosis Using Histopathological Images

  Citation: 142

  Authors: C., S., D., A.

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