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Artificial intelligence in medical sciences and psychologywith application of machine language, computer vision, and NLP techniques /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence in medical sciences and psychologyby Tshepo Chris Nokeri.
其他題名:	with application of machine language, computer vision, and NLP techniques /
作者:	Nokeri, Tshepo Chris.
出版者:	Berkeley, CA :Apress :2022.
面頁冊數:	xi, 173 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Artificial intelligence.
電子資源:	https://doi.org/10.1007/978-1-4842-8217-5
ISBN:	9781484282175$q(electronic bk.)

Artificial intelligence in medical sciences and psychologywith application of machine language, computer vision, and NLP techniques /
Nokeri, Tshepo Chris.

Artificial intelligence in medical sciences and psychologywith application of machine language, computer vision, and NLP techniques /[electronic resource] :by Tshepo Chris Nokeri. - Berkeley, CA :Apress :2022. - xi, 173 p. :ill. (chiefly col.), digital ;24 cm.

Chapter 1: An Introduction to Artificial Intelligence for Medical Sciences and Psychology -- Chapter 2: Realizing Patterns in Diseases with Neural Networks -- Chapter 3: A Case for COVID-19: Considering the Hidden States and Simulation Results -- Chapter 4: Cancer Segmentation with Neural Networks -- Chapter 5: Modelling Magnetic Resonance Imaging and X-Rays by Executing Artificial Neural Networks -- Chapter 6: A Case for COVID-19 CT Scan Segmentation -- Chapter 7 Modelling Clinical Trial Data -- Chapter 8: Medical Record Categorization -- Chapter 9: A Case for Psychology: Factoring and Clustering Personality Dimensions.

Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques. The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification. This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, medical students, and researchers. What You Will Learn Apply artificial neural networks when modelling medical data Know the standard method for Markov decision making and medical data simulation Understand survival analysis methods for investigating data from a clinical trial Understand medical record categorization Measure personality differences using psychological models.

ISBN: 9781484282175$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-8217-5doiSubjects--Topical Terms:

194058
Artificial intelligence.

LC Class. No.: TA347.A78 / N65 2022

Dewey Class. No.: 610.28563

Artificial intelligence in medical sciences and psychologywith application of machine language, computer vision, and NLP techniques /
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520 $a Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques. The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification. This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, medical students, and researchers. What You Will Learn Apply artificial neural networks when modelling medical data Know the standard method for Markov decision making and medical data simulation Understand survival analysis methods for investigating data from a clinical trial Understand medical record categorization Measure personality differences using psychological models.
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