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A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence…

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A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Medicine for Achieving Advancements in Life Sciences covers an interdisciplinary area and is therefore an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. This resource mainly provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development…

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A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Medicine for Achieving Advancements in Life Sciences covers an interdisciplinary area and is therefore an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. This resource mainly provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. This  ebook also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. 349 p.

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Authors expertises affiliations

  • Ambreen Hamadani, Editor. BVSc & AH, MVSc, PhD: “The Use of Artificial Intelligence for the Prediction of Genetic Merit in Animals”. She is currently a Post Doctoral Fellow at the National Institute of Technology, Srinagar, Jammu and Kashmir (India).
  • Nazir A. Ganai, Editor. Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir, Jammu and Kashmir (India).
  • Henna Hamadani, Editor. Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir, Jammu and Kashmir (India). Et al…
  • Publication date (digital version): 2024-04.

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8 July 2024

The expanding scale and complexity of biological data have encouraged a growing use of machine learning in biology to build informative and predictive models of the underlying biological processes. This book contains a comprehensive analysis of the subject.

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