Titlebook: Global Virology III: Virology in the 21st Century; Paul Shapshak,Seetharaman Balaji,John T. Sinnott Book 2019 Springer Nature Switzerland

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引起

Application of Support Vector Machines in Viral Biology,ion of potentially important gene and protein functions. This is mainly due to the highly beneficial aspects of SVM. In this chapter we briefly provide lucid and easy to understand details of SVM algorithms along with applications in virology.

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Eliminating Cervical Cancer: A Role for Artificial Intelligence,pathogenesis and cervical cancer epidemiology; discusses the effectiveness of current primary and secondary prevention strategies and explores the potential role of AI technologies in improving cervical screening, diagnosis and treatment with the goal of eliminating cervical cancer.

出价

Tuberculosis: Advances in Diagnostics and Treatment,hat has become promising is the development of virtual directly observed treatment (VDOT) via video, in areas with broadband internet and affordable devices that reach even remote places with tuberculosis patients. VDOT and drone drug delivery allow the treatment of tuberculosis in areas with minimal resources.

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Surgeon

HIV and Injection Drug Use: New Approaches to HIV Prevention, mental health disorders, and poor access to needle-syringe exchange programs and HIV pre-exposure prophylaxis pose grave challenges to control these epidemics. In this chapter, we focus on the impact of the global injection drug use epidemic as well as new approaches on HIV prevention and the HIV care continuum for people who inject drugs.

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温室

Book 2019ology/astrobiology, plasmids, swarm intelligence, bioinformatics, data-mining, machine learning, neural networks, critical equations, and advances in biohazard biocontainment. Novel and forward-looking methods, techniques, and approaches in research and development are presented by experts in the field. .

借喻

https://doi.org/10.1007/978-3-322-87691-1, we have focused on some of the machine learning techniques in the context of viral disease. In brief, machine learning methods have great potential in drug discovery, drug repurposing, and in precision medicine.

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