BIBFRAME Work

Title

AI in disease detection

Other Titles (e.g. Variant)

Artificial intelligence in disease detection

Type

• Text
• Monograph

Contribution

• Gehlot, Anita (editor)
• Singh, Rajesh, 1980- (editor)
• Akram, Shaik Vaseem (editor)
• Rathour, Navjot (editor)

Subject

• Diagnosis--Data processing (LCSH)
• Artificial intelligence--Medical applications (LCSH)
• Diagnosis--Technological innovations (LCSH)

Language

• English

Classification

• LCC: RC78.7.D35 (Assigner: dlc) (Status: used by assigner)
• DDC: 616.07/50285 (Assigner: dlc)

Content

• text

Supplementary content

• bibliography
• index

Summary

"A comprehensive resource encompassing recent developments and potential uses of AI in disease detection is in tremendous demand. Healthcare professionals, researchers, and students are turning more frequently to artificial intelligence (AI) to improve disease detection and diagnosis, but there is limited availability of readily available, latest resources that offer an in-depth examination of the field. AI in Disease Detection: Advancements and Applications fulfils the demand by offering a practical and broad guide to AI in disease detection. The book explores the fundamental concepts of AI and machine learning in the context of disease detection, the challenges and opportunities associated with using AI in healthcare, and the major applications of AI in disease detection. Healthcare experts, researchers, and students will gain practical skills in evaluating big data for health care, integrating artificial intelligence (AI) methods to medical data, and assessing the social and ethical consequences of AI in healthcare. They will also be able to recognise the essential AI applications in disease detection, enabling these individuals to make informed decisions when incorporating AI into their work or research. Overall, this book presents an overview of the transformation, progression, and applications of AI in disease detection. The book contains substantial findings and practical recommendations for researchers, healthcare professionals, and policymakers interested in studying the ability of AI to boost disease detection and patient outcomes"-- Provided by publisher.

Table of Contents

Introduction to AI in disease detection: an overview of the use of AI in detecting diseases, including the benefits and limitations of the technology / Arvind Singh Rawat, Jagadheswaran Rajendran, Shailendra Singh Sikarwar -- AI in disease surveillance: an overview of how AI can be used in disease surveillance and outbreak detection, including case studies of its use in real-world scenarios / Abhishek Tripathi, Rachna Rathore.

Authorized Access Point

AI in disease detection

Admin Metadata

• Date: 2026-09-11T20:16:37.695442+00:00
• Agent: cbc
• Status: c
• Derived from: 24131141

Admin Metadata

• Date: 2026-09-11
• Cataloger id: Unknown
• Description level: http://id.loc.gov/ontologies/bibframe-2-6-0/
• Description language: eng
• Description authentication: pcc