Computers in Biology and Medicine

Aims & Scope

Computers in Biology and Medicine 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.

The Journal encourages the exchange of important research, instruction, ideas and information on all aspects of the rapidly expanding area of computer usage in these fields.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	6.3
2024	7.00

Journal Rank

Year	Value
2024	2546

Journal Citation Indicator

Year	Value
2024	27878

SJR (SCImago Journal Rank)

Year	Value
2024	1.447

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	142

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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
• Medline
• Embase

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Medicine, 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.

• Automated detection of COVID-19 cases using deep neural networks with X-ray images

  Citation: 2072

  Authors: Tulin, Muhammed, Eylul Azra, Ulas Baran, Ozal, U.

• Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals

  Citation: 1288

  Authors: U. Rajendra, Shu Lih, Yuki, Jen Hong, Hojjat

• A deep convolutional neural network model to classify heartbeats

  Citation: 1139

  Authors: U. Rajendra, Shu Lih, Yuki, Jen Hong, Muhammad, Arkadiusz, Ru San

• Brain tumor classification using deep CNN features via transfer learning

  Citation: 992

  Authors: S., P.M.

• Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images

  Citation: 834

  Authors: Tawsifur, Amith, Yazan, Anas, Serkan, Saad Bin, Mohammad Tariqul, Somaya, Susu M., Muhammad Salman, Muhammad E.H.

• Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks

  Citation: 698

  Authors: Ali Abbasian, Alireza Rajabzadeh, U. Rajendra, Nazanin, Afshin

• Arrhythmia detection using deep convolutional neural network with long duration ECG signals

  Citation: 678

  Authors: Özal, Paweł, Ru-San, U. Rajendra

• A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification

  Citation: 667

  Authors: Özal

• Fractals and the analysis of waveforms

  Citation: 651

  Authors: Michael J.

• A review of feature selection methods in medical applications

  Citation: 609

  Authors: Beatriz, Veronica

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