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Review Article | Artificial Intelligence Applications in Prognosis and Treatment of Neuro-oncology: A review
Adham Al-Rahbi1, Tariq Al-Habsi2, Tariq Al-Saadi3,4
1Anatomical pathology program, Oman Medical Specialty Board, Al-khoudh, Muscat 132, Oman.
Introduction:
Artificial intelligence (AI) is the general term that contains Machine Learning (ML), and Deep Learning (DL). Utilization of these technologies in brain tumor treatment and prognosis is promising.
Aim:
This article aims to review recent applications of AI in neuro-oncology treatment and prognosis. Furthermore, it elucidates the challenges and future directions.
Method:
A comprehensive literature review in four databases (Wiley, Scopus, PubMed, and Google Scholar) gave a total of 21 articles using AI in neuro-oncology treatment and disease prognosis. papers were grouped and reviewed. The data was summarized and presented in tables and graphs. This is the first article to review these two areas of AI in neuro-oncology in a single paper and provide insight into knowledge gaps and future directions.
Results:
Most of the reviewed articles are about prognosis (14 articles). The largest article in sample size (41222) is about the prediction of inpatient Length of Stay (LOS) after brain tumor surgery. They used twenty-nine machine learning algorithms. In articles about the treatment of neuro-oncology, the highest sample size is (1585) in assessment of treatment response using AI algorithms.
Conclusion:
AI technologies implementation in neuro-oncology is crucial. More research and validation of current applications is needed. And careful integration of these technologies is important.
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