<p><span>The authors aim to shed light on the practicality of using machine learning in finding complex chemoinformatics and bioinformatics applications as well as identifiying AI in biological and chemical data points. The chapters are designed in such a way that they highlight the important role o
Ethical Issues in AI for Bioinformatics and Chemoinformatics
โ Scribed by Yashwant V. Pathak (editor), Surovi Saikia (editor), Sarvadaman Pathak (editor), Jayvadan K. Patel (editor)
- Publisher
- CRC Press
- Year
- 2023
- Tongue
- English
- Leaves
- 224
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This unique volume presents AI in relation to ethical points of view in handling big data sets. Issues such as algorithmic biases, discrimination for specific patterns and privacy breaches may sometimes be skewed to affect research results so that certain fields to appear more appealing to funding agencies. The discussion on the ethics of AI is highly complex due to the involvement of many international stakeholders such as the UN, OECD, parliaments, industry groups, professional bodies, and individual companies. The issue of reliability is addressed including the emergence of synthetic life, 5G networks, intermingling of human artificial intelligence, nano-robots and cyber security tools.
Features
- Discusses artificial intelligence and ethics, the challenges and opportunities
- Presents the issue of reliability in the emergence of synthetic life, 5G networks, intermingling of human artificial intelligence, nano-robots, and cyber security tools
- Ethical responsibility and reasoning for using AI in Big Data
- Addresses practicing medicine and ethical issues when applying artificial intelligence
โฆ Table of Contents
Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Editor Biographies
List of Contributors
Chapter 1 Artificial Intelligence and Ethics: Challenges and Opportunities
Chapter 2 Basic Ethical Issues in Bioinformatics and Chemoinformatics
Chapter 3 The Ethical Responsibility and Reasoning for Using AI in Big Data
Chapter 4 Ethical Theories in AI: A Machine Learning Context
Chapter 5 Leave-One-Out Cross-Validation in Machine Learning
Chapter 6 Ethical Issues and Artificial Intelligence Technologies in Bioinformatics Concerning Behavioural and Mental Health Care
Chapter 7 Practicing Medicine and Ethical Issues Applying Artificial Intelligence
Chapter 8 Cybersecurity and Intraoperative Artificial Intelligence Decision Support: Challenges and Solutions Related to Ethical Issues
Chapter 9 Artificial Intelligence and Robots in Individualsโ Lives: How to Align Technological Possibilities and Ethical Issues
Chapter 10 Ethical Issues Using AI in the Field of Pediatrics
Chapter 11 Understanding Data Analysis and Why Should We Do It?
Chapter 12 Disease Diagnostics, Monitoring, and Management by Deep Learning: A Physicianโs Guide in Ethical Issues in NMR Medical Imaging Clinical Trials
Index
๐ SIMILAR VOLUMES
<p><i>Chemoinformatics and Bioinformatics in the Pharmaceutical Sciences</i> brings together two very important fields in pharmaceutical sciences that have been mostly seen as diverging from each other: chemoinformatics and bioinformatics. As developing drugs is an expensive and lengthy process, tec
A breakthrough guide employing knowledge that unites cheminformatics and bioinformatics as innovation for the future </p><p xmlns="http://www.w3.org/1999/xhtml">Bridging the gap between cheminformatics and bioinformatics for the first time, Computational Approaches in Cheminformatics and Bioinformat
<p>A breakthrough guide employing knowledge that unites cheminformatics and bioinformatics as innovation for the future</p><p>Bridging the gap between cheminformatics and bioinformatics for the first time, Computational Approaches in Cheminformatics and Bioinformatics provides insight on how to blen
<p><span>An essential resource on artificial intelligence ethics for business leadersย ย </span></p><p><span>Inย </span><span>Trustworthy AI</span><span>, award-winningย executiveย Beena Ammanathย offers a practical approachย for enterprise leaders to manage business risk in a world where AI is everywhere