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Applied medical statistics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applied medical statisticsJingmei Jiang.
Author:	Jiang, Jingmei,
Published:	Hoboken, NJ :Wiley Blackwell,2022.
Description:	1 online resource (xvii, 565 p.) :ill.
Subject:	MedicineResearch
Online resource:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119716822
ISBN:	9781119716822$q(electronic bk.)

Applied medical statistics
Jiang, Jingmei,1958-

Applied medical statistics[electronic resource] /Jingmei Jiang. - Hoboken, NJ :Wiley Blackwell,2022. - 1 online resource (xvii, 565 p.) :ill.

Includes bibliographical references and index.

"Over the past few decades, biomedical data have proliferated rapidly, and opportunities have arisen to use this data to improve human health. Burgeoning methods, such as machine learning techniques, have emerged to respond to the fast growth of the volume of data, and to exploit data in an effective and efficient manner. These methods were founded on statistical learning theory, which is an expansion of traditional statistics. Therefore, cultivating basic statistical thinking capability plays an important and fundamental role in mastering these state-of-the-art methods and embracing the upcoming big data era, which makes a course of introductory biostatistics an indispensable part of the curriculum for medical students. However, as a branch of mathematics, statistics is characterized by hierarchically organized concepts, but a conceptual understanding of statistics is not always intuitive, which makes biostatistics an obstacle that is regarded as a burden for most medical students"--

ISBN: 9781119716822$q(electronic bk.)Subjects--Topical Terms:

230267
Medicine
--Research

LC Class. No.: R853.S7 / J53 2022

Dewey Class. No.: 610.72/7

National Library of Medicine Call No.: WA 950

Applied medical statistics
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100 1 $a Jiang, Jingmei, $d 1958- $3 960505
245 1 0 $a Applied medical statistics $h [electronic resource] / $c Jingmei Jiang.
260 $a Hoboken, NJ : $b Wiley Blackwell, $c 2022.
300 $a 1 online resource (xvii, 565 p.) : $b ill.
504 $a Includes bibliographical references and index.
520 $a "Over the past few decades, biomedical data have proliferated rapidly, and opportunities have arisen to use this data to improve human health. Burgeoning methods, such as machine learning techniques, have emerged to respond to the fast growth of the volume of data, and to exploit data in an effective and efficient manner. These methods were founded on statistical learning theory, which is an expansion of traditional statistics. Therefore, cultivating basic statistical thinking capability plays an important and fundamental role in mastering these state-of-the-art methods and embracing the upcoming big data era, which makes a course of introductory biostatistics an indispensable part of the curriculum for medical students. However, as a branch of mathematics, statistics is characterized by hierarchically organized concepts, but a conceptual understanding of statistics is not always intuitive, which makes biostatistics an obstacle that is regarded as a burden for most medical students"-- $c Provided by publisher.
588 $a Description based on print version record.
650 0 $a Medicine $x Research $x Statistical methods $3 230267
650 0 $a Medical statistics $v Examinations, questions, etc. $3 438641
650 0 $a Biometry $3 318423
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650 2 $a Statistics as Topic. $3 267172
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119716822