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Titlebook: Machine Learning in Biological Sciences; Updates and Future P Shyamasree Ghosh,Rathi Dasgupta Book 2022 The Editor(s) (if applicable) and T

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發(fā)表于 2025-3-21 18:46:02 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Machine Learning in Biological Sciences
副標(biāo)題Updates and Future P
編輯Shyamasree Ghosh,Rathi Dasgupta
視頻videohttp://file.papertrans.cn/621/620658/620658.mp4
概述Gives an overview of machine learning methods, models and different applications in life sciences.Describes the use of ML in studying animal behavior, plant-pathogen interaction.Discusses the future o
圖書(shū)封面Titlebook: Machine Learning in Biological Sciences; Updates and Future P Shyamasree Ghosh,Rathi Dasgupta Book 2022 The Editor(s) (if applicable) and T
描述.This book gives an overview of applications of Machine?Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences.?Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine.?This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which?forms a major domain of?research?in the field of biology.??..It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences..
出版日期Book 2022
關(guān)鍵詞machine learning; artificial intelligence; computational biology; systems biology; biomedicine; neural ne
版次1
doihttps://doi.org/10.1007/978-981-16-8881-2
isbn_softcover978-981-16-8883-6
isbn_ebook978-981-16-8881-2
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Neural Network and Deep Learning,nalyze how handwritten digits can be recognized effectively using neural network techniques. Neural network as a part of statistical learning methods evolved more than 50 years and it got new energy because of application in understanding complex processes in Physics and Life Sciences.
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Machine Learning and Epilepsy,ing is enabling early, better and accurate diagnosis and hence?enabling decision making in therapy and holds great promise in this field of biomedical research. We discuss in this chapter the different applications of machine learning in understanding the biomedical aspects of epilepsy.
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,The?IT Industry and Applications in Biology,learning in applications to health, understanding Trends of disease, analysis of psychological and emotional health, from social networking sites like facebook, analysis of sequencing data using PyTorch algorithm.
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Book 2022 agriculture, and plant sciences.?Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medi
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