Personalized cancer treatment; How AI is shaping precision medicine

The application of artificial intelligence has demonstrated promising outcomes in certain areas of oncology, such as the screening, detection, diagnosis, treatment, and prediction of prognosis for tumors. New learning methods, such as the hybrid learning method, will continue to emerge as artificial intelligence (AI) continues to advance, computer performance continues to improve, and the explosion of various data continues to make it possible for new learning methods to emerge. These new learning methods will further improve the overall performance of the model, including efficient data analysis and accurate prediction. Both machine learning and deep learning have recently produced a model that is capable of analyzing a variety of data sets, which will also boost the prospects of PM. As a conclusion, artificial intelligence-assisted prenatal care has the potential to aid in the early detection, diagnosis, and treatment of cancer. Additionally, it can provide assistance in the selection of the most appropriate treatment plan, so enhancing the prognosis of patients and the outcomes of their treatment.

Authors

Publication Details

Journal
World Journal of Biology Pharmacy and Health Sciences
Published
2024-09-15
DOI
https://doi.org/10.30574/wjbphs.2024.19.3.0622
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.40
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article

Personalized cancer treatment; How AI is shaping precision medicine

Nikolaos Tzenios, Kimberly Morton Cuthrell, Mehrab Manteghian
1 citations
World Journal of Biology Pharmacy and Health Sciences
Radiomics and Machine Learning in Medical Imaging
0.40
article

Personalized cancer treatment; How AI is shaping precision medicine

Nikolaos Tzenios, Kimberly Morton Cuthrell, Mehrab Manteghian
article en
1 citations

Abstract

The application of artificial intelligence has demonstrated promising outcomes in certain areas of oncology, such as the screening, detection, diagnosis, treatment, and prediction of prognosis for tumors. New learning methods, such as the hybrid learning method, will continue to emerge as artificial intelligence (AI) continues to advance, computer performance continues to improve, and the explosion of various data continues to make it possible for new learning methods to emerge. These new learning methods will further improve the overall performance of the model, including efficient data analysis and accurate prediction. Both machine learning and deep learning have recently produced a model that is capable of analyzing a variety of data sets, which will also boost the prospects of PM. As a conclusion, artificial intelligence-assisted prenatal care has the potential to aid in the early detection, diagnosis, and treatment of cancer. Additionally, it can provide assistance in the selection of the most appropriate treatment plan, so enhancing the prognosis of patients and the outcomes of their treatment.

World Journal of Biology Pharmacy and Health SciencesVol. 19(3)
Openalex Percentile: Top 34%
Radiomics and Machine Learning in Medical Imaging
0.40
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Personalized cancer treatment; How AI is shaping precision medicine — Nikolaos Tzenios, Kimberly Morton Cuthrell, et al. · World Journal of Biology Pharmacy and Health Sciences (2024) | TGRS Research Map | TGRS