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Journal Photo for Computers in Biology and Medicine
Peer reviewed only Open Access

Computers in Biology and Medicine (CBM)

Publisher : Elsevier BV
Biomedical Biology Medicine
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e-ISSN 1879-0534
p-ISSN 0010-4825
Issue Frequency Monthly
Impact Factor 7.0
Est. Year 1970
Mobile 441865610674
Country United Kingdom
Language English
APC YES
Impact Factor Assignee Google Scholar
Email l.brett@elsevier.com

Journal Descriptions

Computers in Biology and Medicine, a companion title to Informatics in Medicine Unlocked, is a medium of international communication of the revolutionary advances being made in the application of the computer to the fields of bioscience and medicine. Articles which examine the following topics of special interest are being featured in Computers in Biology and Medicine: Computer aids to the analysis of biochemical systems, computer aids to biocontrol-systems engineering, neuronal simulation by digital-computer gating components, automatic computer analysis of pictures of biological and medical importance, use of computers by commercial pharmaceutical and chemical organizations, radiation-dosage computers, and accumulating and recalling individual medical records, real-time languages, interfaces to patient monitors, clinical chemistry equipment, data handling and display in nuclear medicine and therapy.

Computers in Biology and Medicine (CBM) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Biomedical, Biology, Medicine, Data Processing, Bioinformatics, Computer Science Applications, Health Informatics , Online or Print , Monthly Journal

  • UGC Approved, ISSN Approved: P-ISSN P-ISSN: 0010-4825, E-ISSN: 1879-0534, Established: 1970, Impact Factor: 7.0
  • Does Not Provide Crossref DOI

  • Indexed in: Scopus, WoS

  • Not indexed in DOAJ, PubMed, UGC CARE

Indexing

Publications of CBM

FP-CNN: Fuzzy pooling-based convolutional neural network for lung ultrasound image classification with explainable AI
Mohammad Ali Moni October, 2023
The COVID-19 pandemic wreaks havoc on healthcare systems all across the world. In pandemic scenarios like COVID-19, the applicability of diagnostic modalities is crucial in medical diagnosis...
The pathogenetic influence of smoking on SARS-CoV-2 infection: Integrative transcriptome and regulomics analysis of lung epithelial cells
Mohammad Ali Moni June, 2023
Corona virus disease (COVID-19) has been emerged as pandemic infectious disease. The recent epidemiological data suggest that the smokers are more vulnerable to infection with COVID-19; howe...
An integrated in-silico Pharmaco-BioInformatics approaches to identify synergistic effects of COVID-19 to HIV patients
Mohammad Ali Moni March, 2023
Background With high inflammatory states from both COVID-19 and HIV conditions further result in complications. The ongoing confrontation between these two viral infections can be avoided b...
PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning
Mohammad Ali Moni January, 2023
Despite the arsenal of existing cancer therapies, the ongoing recurrence and new cases of cancer pose a serious health concern that necessitates the development of new and effective treatmen...
A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models
Mohammad Ali Moni July, 2022
The brain tumor is one of the deadliest cancerous diseases and its severity has turned it to the leading cause of cancer related mortality. The treatment procedure of the brain tumor depends...
NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides
Mohammad Ali Moni September, 2022
Tumor homing peptides (THPs) play a crucial role in recognizing and specifically binding to cancer cells. Although experimental approaches can facilitate the precise identification of THPs, ...
SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins
Mohammad Ali Moni July, 2022
Thermophilic proteins (TPPs) are important in the field of protein biochemistry and development of new enzymes. Thus, computational methods must be urgently developed to accurately and rapid...
DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins
Mohammad Ali Moni June, 2022
Accurate identification of DNA-binding proteins (DBPs) is critical for both understanding protein function and drug design. DBPs also play essential roles in different kinds of biological ac...
A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images
Mohammad Ali Moni December, 2021
Coronavirus disease-19 (COVID-19) is a severe respiratory viral disease first reported in late 2019 that has spread worldwide. Although some wealthy countries have made significant progress ...
Machine learning-based statistical analysis for early stage detection of cervical cancer
Mohammad Ali Moni December, 2021
Cervical cancer (CC) is the most common type of cancer in women and remains a significant cause of mortality, particularly in less developed countries, although it can be effectively treated...