A bibliometrics analysis based on the application of artificial intelligence in the field of radiotherapy from 2003 to 2023
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.This bibliometric study analyzes artificial intelligence (AI) and radiotherapy (RT) research from 2003-2023. Key trends include the rise of deep learning and machine learning in RT applications.
Area Of Science
- Medical Physics
- Oncology
- Radiotherapy
Background
- Artificial intelligence (AI) is increasingly used in radiotherapy (RT) to improve tumor treatment.
- Bibliometric studies on the intersection of AI and RT are lacking.
- This study provides an overview of AI and RT research structure and trends.
Purpose Of The Study
- To conduct a bibliometric analysis of publications on artificial intelligence (AI) and radiotherapy (RT).
- To identify knowledge structure, research hotspots, and trends in AI and RT.
- To offer a resource for researchers interested in AI applications in RT.
Main Methods
- A comprehensive search was performed on the Web of Science Core Collection (WoSCC) database from 2003 to 2023.
- Bibliometric analysis was conducted using VOSviewers, CiteSpace, and the R package 'bibliometrix'.
- Data from 615 publications across 64 countries were analyzed.
Main Results
- Publication output on AI and RT has grown annually since 2017, with the USA and China as leading contributors.
- Maastricht University was the most prolific research institution; Frontiers in Oncology published the most articles, while Medical Physics received the most citations.
- Key research hotspots include 'autocontouring algorithm', 'deep learning', and 'machine learning'.
Conclusions
- The bibliometric analysis offers valuable insights into current research directions and advancements in AI for RT.
- This study serves as a crucial resource for academics seeking to understand the evolving landscape of AI in radiotherapy.
- It highlights emerging research frontiers and trending topics within AI and RT.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
Cancer therapies are various modes of treatment, such as surgery, radiation therapy, and chemotherapy that are administered to cancer patients.
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...