Artificial Intelligence and Bioinformatics in Cancer: An Interdisciplinary Approach
The “Artificial Intelligence and Bioinformatics in Cancer: An Interdisciplinary Approach” is the eighteenth volume of the “Interdisciplinary Cancer Research” series, publishes comprehensive volume on the advances of machine learning and bioinformatics in cancer. The volume starts with a chapter on a...
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| מחברים אחרים: | |
| פורמט: | אלקטרוני ספר אלקטרוני |
| שפה: | אנגלית |
| יצא לאור: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| מהדורה: | 1st ed. 2025. |
| סדרה: | Interdisciplinary Cancer Research,
18 |
| נושאים: | |
| גישה מקוונת: | https://doi.org/10.1007/978-3-031-92206-0 |
| תגים: |
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תוכן הענינים:
- Digital Pathology and Artificial Intelligence for Early Diagnosis of Pediatric Solid Tumors: Implication For Improved Healthcare Strategies
- Digital Health Technologies in Cancer Care and Research
- Unveiling Cancer Complexity: Machine Learning Insights into Multi-Omics Data
- The Role of Integrated Bioinformatics in Cancer Research: Transforming Genomic Insights into Precision Medicine
- In Silico and Biophysical Techniques in Anticancer Drug Discovery Research
- In Silico Methods and Targeted Receptors Used in Cancer Studies
- Modeling Uncertain Growth and Diffusion in Cancer Tumors with Heterogeneous Cell Mutations
- Imaging Tumor Metabolism and Its Heterogeneity: Special Focus on Radiomics and AI
- Mathematical Modeling of Cancer Tumor Dynamics with Multiple Fuzzification Approaches in Fractional Environment
- Is Cancer Our Equal or Our Better? Artificial Intelligence in Cancer Drug Discovery
- Recent Advances in Artificial Intelligence and Cancer Treatment
- Signature-Based Drug Repositioning: Tackling Speeding Up Drug Discovery of Anticancer Drugs Employing Recently Developed Machine Learning Tools
- Mathematical Analysis of Cancer-Tumor Models with Variable Depression Effects and Integrated Treatment Strategies
- Emerging Role of Artificial Intelligence in Colorectal Cancer: Screening and Diagnosis
- Measuring the Performance of Supervised Machine Learning Approaches Using Cancer Data
- VRTumor: Integrating AI-Based Segmentation with Virtual Reality for Precise Tumor Analysis. Artificial Intelligence Applications to Detect Pediatric Brain Tumor Biomarkers.