Titlebook: Computational Intelligence in Oncology; Applications in Diag Khalid Raza Book 2022 The Editor(s) (if applicable) and The Author(s), under e

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Predicting Biomarkers and Therapeutic Targets in Cancerlp in guiding the medical oncologists in the selection of anti-cancer treatment for a person suffering from cancer. Also, it helps in calculating the improvable of the toxicity to benefit ratio. The success of this treatment is due to the emergence of predictive biomarkers. A predictive biomarker is

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Computational Intelligence in Oncology: Past, Present, and Futurecology, computational Oncology, roles of CI in various aspects of oncology research including classification, Prediction, risk analysis, therapy, optimized cancer treatment, management, etc. It also describes the current trends and future of CI in oncology research.

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Predicting the Cancer Recurrence Using Artificial Neural Networkschines (SVMs), artificial neural networks (ANNs), and conventional neural networks (CNNs). The recurrence of cancer is also an important issue that needs to be predicted with significant accuracy. This chapter reviews current state-of-the-art of ANNs model in the prediction of cancer recurrence.

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