Artificial Intelligence in Cancer Diagnosis and Therapy
Cancer is the second leading cause of death worldwide. According to the World Health Organisation (WHO), around 10 million people died from cancer globally in 2020. Early detection of cancer is of utmost importance for the effective treatment and prevention of the spread of cancer cells to other parts of the body (Metastasis). Artificial Intelligence (AI) has been revolutionizing discovery, diagnosis, and treatment designs. It can aid not only in cancer detection but also in cancer therapy design, identification of new therapeutic targets with accelerating drug discovery, and in improving cancer surveillance when analyzing patient and cancer statistics. AI-guided cancer care could also be effective in clinical screening and management with better health outcomes. The Machine Learning (ML) algorithms developed based on biological and computer sciences can significantly help scientists in facilitating discovery process of biological systems behind cancer initiation, growth, and metastasis. They can be also used by physicians and surgeons in the effective diagnosis and treatment design for different types of cancer and for biotechnology and pharmaceutical industries in carrying out more efficient drug discovery.
Dr. Hamid Khayyam
Dr. Ali Madani
Dr. Rahele Kafieh
Prof. Dr. Ali Hekmatnia
- artificial intelligence
- machine learning
- modeling complex biological systems
- computational cancer biology
- computational drug discovery
- radiation therapy (oncology)
- cancer diagnosis and cancer therapy
|Journal Name||Impact Factor||CiteScore||Launched Year||First Decision (median)||APC|
|-||-||2020||21.8 Days||CHF 1200|
|5.2||7.4||2009||18.2 Days||CHF 2900|
|2.6||2.6||1994||18.4 Days||CHF 2200|
|3.6||3.6||2011||18.8 Days||CHF 2600|
|-||-||2021||15.0 days *||CHF 1000|
* Median value for all MDPI journals in the first half of 2023.
Preprints is a platform dedicated to making early versions of research outputs permanently available and citable. MDPI journals allow posting on preprint servers such as Preprints.org prior to publication. For more details about reprints, please visit https://www.preprints.org.