Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Mouse Models of Cancer Study

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...

Cancer

Cancer

Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Bibliometric Analysis of Artificial Intelligence in Pediatric Radiology and Medical Imaging: A Focus on Deep Learning Applications.

Bioengineering (Basel, Switzerland)·2026

Same author

Artificial Intelligence (AI) in Saxitoxin Research: The Next Frontier for Understanding Marine Dinoflagellate Toxin Biosynthesis and Evolution.

Toxins·2026

Same author

CNN-ViT Supported Weakly-Supervised Video Segment Level Anomaly Detection.

Sensors (Basel, Switzerland)·2023

Same author

Emotional arousal pattern (EMAP): A new database for modeling momentary subjective and psychophysiological responding to affective stimuli.

Psychophysiology·2023

Same author

Prediction of moment-by-moment heart rate and skin conductance changes in the context of varying emotional arousal.

Psychophysiology·2023

Same author

ERCP: Energy-Efficient and Reliable-Aware Clustering Protocol for Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2022

Search research articles

Related Experiment Video

Updated: May 5, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Vision-Language Models in Medical Imaging for Cancer Diagnosis: A Bibliometric Review.

Musa Adamu Wakili¹, Aminu Bashir Suleiman^2,3, Kaloma Usman Majikumna⁴

¹Department of Artificial Intelligence, Abubakar Tafawa Balewa University, Bauchi 740272, Nigeria.

Bioengineering (Basel, Switzerland)

|May 4, 2026

Summary

Multimodal artificial intelligence (AI) is advancing cancer diagnosis by integrating imaging and text data. This bibliometric analysis shows rapid growth in AI research for cancer detection and staging, shifting towards explainable and multimodal methods.

Keywords:

bibliometric analysis cancer diagnosis medical imaging multimodal AI vision–language models

More Related Videos

Using Computer-based Image Analysis to Improve Quantification of Lung Metastasis in the 4T1 Breast Cancer Model

Using Computer-based Image Analysis to Improve Quantification of Lung Metastasis in the 4T1 Breast Cancer Model

Published on: October 2, 2020

A Permanent Window for Investigating Cancer Metastasis to the Lung

A Permanent Window for Investigating Cancer Metastasis to the Lung

Published on: July 1, 2021

Related Experiment Videos

Last Updated: May 5, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Using Computer-based Image Analysis to Improve Quantification of Lung Metastasis in the 4T1 Breast Cancer Model

Using Computer-based Image Analysis to Improve Quantification of Lung Metastasis in the 4T1 Breast Cancer Model

Published on: October 2, 2020

A Permanent Window for Investigating Cancer Metastasis to the Lung

A Permanent Window for Investigating Cancer Metastasis to the Lung

Published on: July 1, 2021

Area of Science:

Artificial Intelligence in Medicine
Medical Imaging Analysis
Bibliometrics

Background:

Traditional deep learning models in medical imaging lack explainability and multimodal reasoning.
There is a growing need for advanced cancer detection and staging methods.
Multimodal approaches integrating visual and textual data are emerging to improve accuracy and interpretability.

Purpose of the Study:

To conduct a bibliometric analysis of research on multimodal artificial intelligence in cancer diagnosis.
To map citation networks, co-authorship, and keyword co-occurrences in this field.
To identify key trends, emerging themes, and research gaps.

Main Methods:

Bibliometric analysis of 408 publications (2021-2025) from Web of Science and Scopus.
Utilized VOSviewer and R-Bibliometrix for data analysis.
Thematic analysis of research trends and methodologies.

Main Results:

Rapid publication growth observed, from 1 in 2021 to 269 in 2025.
Significant contributions from leading countries and institutions identified.
Shift from convolutional neural networks to transformer-based and self-supervised learning methods noted.
Increasing focus on multimodal learning for breast, lung, and brain cancer imaging.

Conclusions:

Multimodal AI is a rapidly growing field in cancer diagnosis.
Research is shifting towards more explainable and interpretable AI models.
Future research should focus on addressing identified research gaps in multimodal AI for cancer imaging.