Optimized Predictive Models in Health Care Using Machine Learning

Kumar, Sandeep, Sharma, Anuj, Kaur, Navneet

Optimized Predictive Models in Health Care Using Machine Learning
  • 出版商: Wiley-Scrivener
  • 出版日期: 2024-03-12
  • 售價: $6,660
  • 貴賓價: 9.5 折 $6,327
  • 語言: 英文
  • 頁數: 384
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1394174624
  • ISBN-13: 9781394174621
  • 相關分類: Machine Learning

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商品描述

OPTIMIZED PREDICTIVE MODELS IN HEALTH CARE USING MACHINE LEARNING

This book is a comprehensive guide to developing and implementing optimized predictive models in healthcare using machine learning and is a required resource for researchers, healthcare professionals, and students who wish to know more about real-time applications.

The book focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity and provides content on the theory of optimized predictive model design, evaluation, and user diversity. Predictive modeling, a field of machine learning, has emerged as a powerful tool in healthcare for identifying high-risk patients, predicting disease progression, and optimizing treatment plans. By leveraging data from various sources, predictive models can help healthcare providers make informed decisions, resulting in better patient outcomes and reduced costs.

Other essential features of the book include:

  • provides detailed guidance on data collection and preprocessing, emphasizing the importance of collecting accurate and reliable data;
  • explains how to transform raw data into meaningful features that can be used to improve the accuracy of predictive models;
  • gives a detailed overview of machine learning algorithms for predictive modeling in healthcare, discussing the pros and cons of different algorithms and how to choose the best one for a specific application;
  • emphasizes validating and evaluating predictive models;
  • provides a comprehensive overview of validation and evaluation techniques and how to evaluate the performance of predictive models using a range of metrics;
  • discusses the challenges and limitations of predictive modeling in healthcare;
  • highlights the ethical and legal considerations that must be considered when developing predictive models and the potential biases that can arise in those models.

Audience

The book will be read by a wide range of professionals who are involved in healthcare, data science, and machine learning.

商品描述(中文翻譯)

《使用機器學習在醫療保健中優化的預測模型》

本書是一本全面的指南，旨在開發和實施使用機器學習的優化預測模型，是研究人員、醫療專業人員和希望了解實時應用的學生所需的資源。

本書重點介紹人類與計算機之間如何在日益增長的複雜性和簡單性中互動，並提供有關優化預測模型設計、評估和用戶多樣性的理論內容。預測建模作為機器學習的一個領域，已成為醫療保健中識別高風險患者、預測疾病進展和優化治療計劃的強大工具。通過利用來自各種來源的數據，預測模型可以幫助醫療提供者做出明智的決策，從而改善患者結果並降低成本。

本書的其他重要特點包括：
- 提供有關數據收集和預處理的詳細指導，強調收集準確和可靠數據的重要性；
- 解釋如何將原始數據轉換為有意義的特徵，以提高預測模型的準確性；
- 詳細概述醫療保健中用於預測建模的機器學習算法，討論不同算法的優缺點以及如何為特定應用選擇最佳算法；
- 強調驗證和評估預測模型的重要性；
- 提供驗證和評估技術的全面概述，以及如何使用各種指標評估預測模型的性能；
- 討論醫療保健中預測建模的挑戰和局限性；
- 突出在開發預測模型時必須考慮的倫理和法律問題，以及這些模型中可能出現的潛在偏見。

讀者對象

本書將被廣泛的專業人士閱讀，他們涉及醫療保健、數據科學和機器學習領域。

作者簡介

Sandeep Kumar, PhD, is a professor in the Department of Computer Science and Engineering, K L Deemed to be University, Vijayawada, Andhra Pradesh, India. He has been granted six patents and successfully filed another ten. He has published more than 100 research papers in various national and international journals and proceedings of reputed national and international conferences.

Anuj Sharma, PhD, is a professor at Maharshi Dayanand University, Rohtak, India. He has 19 years of teaching and administrative experience and has published more than 50 journal articles.

Navneet Kaur, PhD, is a professor in the Department of Computer Science & Engineering, Chandigarh University, India. She is the awardee of the Best Engineering College Teacher Award for Punjab State for the year 2019 and has published more than 35 research articles in reputed SCI journals and conferences.

Lokesh Pawar, PhD, is an assistant professor at Chandigarh University, India. He has filed two patents and has published multiple research articles in many SCI journals.

Rohit Bajaj, PhD, is an associate professor in the Department of Computer Science & Engineering, Chandigarh University, India. He has 12 years of teaching research experience and has published 60 papers in refereed journals and conferences.

作者簡介(中文翻譯)

Sandeep Kumar, PhD，是印度安得拉邦維賈亞瓦達K L Deemed to be University計算機科學與工程系的教授。他已獲得六項專利，並成功申請了另外十項。他在各種國內外期刊及知名國際會議的論文集中發表了超過100篇研究論文。

Anuj Sharma, PhD，是印度羅哈特克的Maharshi Dayanand University的教授。他擁有19年的教學和行政經驗，並發表了超過50篇期刊文章。

Navneet Kaur, PhD，是印度昌迪加爾大學計算機科學與工程系的教授。她於2019年獲得旁遮普州最佳工程學院教師獎，並在知名SCI期刊和會議上發表了超過35篇研究文章。

Lokesh Pawar, PhD，是印度昌迪加爾大學的助理教授。他已申請兩項專利，並在多個SCI期刊上發表了多篇研究文章。

Rohit Bajaj, PhD，是印度昌迪加爾大學計算機科學與工程系的副教授。他擁有12年的教學研究經驗，並在經過審核的期刊和會議上發表了60篇論文。

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