Genetics Research

Application of Artificial Intelligence Algorithms in Cancer Research


Publishing date
01 Mar 2023
Status
Closed
Submission deadline
21 Oct 2022

Lead Editor
Guest Editors

1Shandong University, Jinan, China

2Union Hospital, Tongji Medical College, Wuhan, China

3Thiruvalluvar University, Vellore, India

This issue is now closed for submissions.

Application of Artificial Intelligence Algorithms in Cancer Research

This issue is now closed for submissions.

Description

Cancer is the leading cause of death worldwide. Despite significant progress in the fight against this disease, it remains a critical public health problem and a substantial burden on our society. It is predicted that by 2040, there will be 2,750 new cases of cancer worldwide each year. As a class of clinical diseases with complex diagnosis, treatment and prognosis, researchers have not found a practical and feasible strategy so far. With the development of high-throughput sequencing technologies, multi-omics data on cancer has become available. This data provides researchers with more opportunities to explore the genetic risk, regulatory mechanisms, and protein functions of cancer.

However, effectively utilizing this data and mining knowledge remains a considerable challenge. Artificial intelligence algorithms have great potential to process omics data and reveal cancer mechanisms. Many artificial intelligence algorithms have been developed and applied in cancer research. With the help of biomarkers identified by artificial intelligence algorithms, oncologists can diagnose cancer early at its onset. In addition, the identification of potential biomarkers facilitates the discovery, design, and application of targeted drugs against cancer.

This Special Issue welcomes researchers to contribute original research and review articles related to artificial intelligence algorithms relevant to cancer diagnosis, treatment, and prognosis.

Potential topics include but are not limited to the following:

  • Artificial intelligence (AI) algorithms for diagnosing, treating, and determining prognosis in cancer
  • AI algorithms to identify cancer pathogenesis
  • Validating the results of AI algorithms through wet lab experiments
  • Clinical application of artificial intelligence algorithms in cancer
  • Application of artificial intelligence algorithms in the development of anticancer drugs
  • Methods for integrating digital/computational pathology and sequencing data in cancer
Genetics Research
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Acceptance rate6%
Submission to final decision117 days
Acceptance to publication17 days
CiteScore0.100
Journal Citation Indicator0.270
Impact Factor1.5
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