Artificial Intelligence and Computational Dynamics for Biomedical Research
1st Edition
Published on 7. November 2022
VI, 292 pages
978-3-11-076204-4 (ISBN)
Description
This work presents the latest development in the field of computational intelligence to advance Big Data and Cloud Computing concerning applications in medical diagnosis. As forum for academia and professionals it covers state-of-the-art research challenges and issues in the digital information & knowledge management and the concerns along with the solutions adopted in these fields.
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Ankur Saxena | Nicolas Brault
Artificial Intelligence and Computational Dynamics for Biomedical Research
E-Book
11/2022
1st Edition
De Gruyter
€169.95
Available for download
Ankur Saxena | Nicolas Brault
Artificial Intelligence and Computational Dynamics for Biomedical Research
Book
11/2022
1st Edition
De Gruyter
€169.95
Shipment within 7-9 days
Persons
Ankur Saxena
, Amity University, India;
Nicolas Brault
, UniLaSalle, Beauvais, France.
Content
- Intro
- Contents
- Recent advancements in biomedical research in the era of AI and ML
- Prediction of cardiovascular diseases using random forest and naive Bayes algorithm
- Big data analytics for personalized medicine
- Intellection of biological life in current era
- Integrating artificial intelligence techniques for analysis of next-generation sequencing data
- Artificial intelligence: the future of neuroscience
- Role of big data and artificial intelligence for COVID-19 and cancer diagnosis and treatments
- Integrating screening modalities for early and precision-oriented evidence-based screening of cervical cancer - a holistic approach
- Role of artificial intelligence and machine learning in diagnosis and treatment of women centric cancer
- The role of artificial intelligence, machine learning and deep learning in the diagnosis, prognosis and treatment of cancers primarily associated with women
- Oropharyngeal cancer prognosis based on clinicopathologic and quantitative imaging biomarkers with multiparametric model and machine learning methods
- Artificial intelligence and machine learning in healthcare: an ethical perspective
- Artificial intelligence in dentistry: current issues and perspectives
- AI for pattern recognition and objectivity: the case of melanoma detection
- Ethical horizons of biobank-based artificial intelligence in biomedical research
- Index
