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Computers in Biology and Medicine (CBM)

Publisher :

Elsevier BV

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Biomedical
  • Biology
  • Medicine

    • +4

e-ISSN :

1879-0534

Issue Frequency :

Monthly

Impact Factor :

7.0

p-ISSN :

0010-4825

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 - 0010-4825, E-ISSN - 1879-0534, Established in - 1970, Impact Factor - 7.0

Not Provide Crossref DOI

Indexed in Scopus, WoS

Not indexed in DOAJ, PubMed, UGC CARE

Indexing

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Scopus
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WoS
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Elsevier

+6 More

Publications of CBM

  • dott image October, 2023

FP-CNN: Fuzzy pooling-based convolutional neural network for lung ultrasound image classification with explainable AI

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...

  • dott image June, 2023

The pathogenetic influence of smoking on SARS-CoV-2 infection: Integrative transcriptome and regulomics analysis of lung epithelial cells

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...

  • dott image March, 2023

An integrated in-silico Pharmaco-BioInformatics approaches to identify synergistic effects of COVID-19 to HIV patients

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...

  • dott image January, 2023

PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning

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...

  • dott image July, 2022

A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models

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...

  • dott image September, 2022

NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides

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, ...

  • dott image July, 2022

SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins

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...

  • dott image June, 2022

DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins

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...

  • dott image December, 2021

A deep learning approach using effective preprocessing techniques to detect COVID-19 from chest CT-scan and X-ray images

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 ...

  • dott image December, 2021

Machine learning-based statistical analysis for early stage detection of cervical cancer

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...

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