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{ "item_title" : "Machine Learning and Computational Studies in Cancer", "item_author" : [" Nima Rezaei "], "item_description" : "Machine Learning and Computational Studies in Cancer: An Interdisciplinary Approach is the thirtieth volume of the Interdisciplinary Cancer Research series, and a comprehensive volume on machine learning and computational studies in cancer research. The volume explores the transformative role of artificial intelligence, machine learning, and computational methods in advancing cancer research and precision oncology. It brings together contributions on computational diagnostics and biomarkers, predictive modeling, systems and quantitative approaches to understanding cancer complexity, multi-omics and bioinformatics analyses, and AI-enabled innovations in cancer research. This is the main concept of the Cancer Immunology Project (CIP), which is a part of the Universal Scientific Education and Research Network (USERN). This interdisciplinary book will be of special value for those who wish to have an update on machine learning and computational studies in cancer.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/03/238/792/3032387922_b.jpg", "price_data" : { "retail_price" : "219.99", "online_price" : "219.99", "our_price" : "219.99", "club_price" : "219.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning and Computational Studies in Cancer|Nima Rezaei

Machine Learning and Computational Studies in Cancer : An Interdisciplinary Approach

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Overview

"Machine Learning and Computational Studies in Cancer: An Interdisciplinary Approach" is the thirtieth volume of the "Interdisciplinary Cancer Research" series, and a comprehensive volume on machine learning and computational studies in cancer research.

The volume explores the transformative role of artificial intelligence, machine learning, and computational methods in advancing cancer research and precision oncology. It brings together contributions on computational diagnostics and biomarkers, predictive modeling, systems and quantitative approaches to understanding cancer complexity, multi-omics and bioinformatics analyses, and AI-enabled innovations in cancer research.

This is the main concept of the Cancer Immunology Project (CIP), which is a part of the Universal Scientific Education and Research Network (USERN). This interdisciplinary book will be of special value for those who wish to have an update on machine learning and computational studies in cancer.

This item is Non-Returnable

Details

  • ISBN-13: 9783032387929
  • ISBN-10: 3032387922
  • Publisher: Springer
  • Publish Date: November 2026
  • Page Count: 311

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