Advances in Cancer Detection, Prediction, and Prognosis Using Artificial Intelligence and Machine Learning

This book covers all aspects of computational biology in studying cancer diagnosis and prognosis, including newer applications involving infection and inflammation, as well as basic information on advanced simulation techniques. It describes the different tools, risk-based modeling techniques, early...

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Bibliografske podrobnosti
Korporativna značnica:	SpringerLink (Online service)
Drugi avtorji:	Nema, Rajeev (Editor), Kumar, Ashok (Editor), Saini, Dinesh Kumar (Editor)
Format:	Elektronski eKnjiga
Jezik:	angleščina
Izdano:	Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Izdaja:	1st ed. 2025.
Teme:	Cancer > Genetic aspects. Cancer. Bioinformatics. Biomathematics. Machine learning. Oncology. Cancer Genetics and Genomics. Cancer Biology. Mathematical and Computational Biology. Machine Learning.
Online dostop:	https://doi.org/10.1007/978-981-96-9346-7
Oznake:	Označite Brez oznak, prvi označite!

Kazalo:

-- Chapter 1: Cancer Diagnosis: An overview
Chapter 2: Computational Methods in Oncology
Chapter 3: Overview of Computational Approaches for Cancer Diagnosis
Chapter 4: Artificial intelligence and Machine Learning in improving diagnostic accuracy
Chapter 5: Advances in Image Processing and Pattern Recognition
Chapter 6: Genomics and Bioinformatics in the discovery and validation of diagnostic biomarkers
Chapter 7: Computer-based wearable devices for remote patient monitoring.
Chapter 8: Overview of computational approaches for Cancer Prognosis
Chapter 9: Predictive Modeling for Cancer Prognosis
Chapter 10:Genomics and Transcriptomics based predictive and prognostic biomarkers
Chapter 11:Artificial Intelligence in Personalized Medicine and Treatment Planning
Chapter 12:Integrative Multi-Omics Approaches
Chapter 13:Challenges and Limitations of Computational Methods in Oncology
Chapter 14:Challenges in Integration of computational approaches with Clinical Practice
Chapter 15:Emerging Technologies in Computational Oncology
Chapter 16:Statement On the Effectiveness of AI And ML In Cancer Care
Chapter 17:Future Directions in Computational Cancer Research
Chapter 18:Deep learning algorithms to analyze medical images for early detection of cancer
Chapter 19:Ethical considerations regarding patient privacy and data security
Chapter 20:Call for further research and implementation of deep learning technologies in oncology for enhanced healthcare delivery.

Advances in Cancer Detection, Prediction, and Prognosis Using Artificial Intelligence and Machine Learning

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