Identification of paget disease in the human body using artificial intelligence and machine learning

Palvi Sharma; Rakesh Kumar; Meenu Gupta

doi:10.1016/b978-0-443-32892-3.00006-3

Identification of paget disease in the human body using artificial intelligence and machine learning

Palvi Sharma
, Rakesh Kumar
, Meenu Gupta

Model Institute of Engineering and Technology
Chandigarh University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Abstract

A chronic bone condition called Paget's disease is characterized by irregular bone restructuring that can results in fractures, deformities, and other difficulties that affect the quality of life. For effective management and treatment, early detection and accurate diagnosis are essential. The detection of Paget's disorder using medical imaging can be enhanced with the help of artificial intelligence (AI) and machine learning (ML) technology. In this work, the potential uses of AI and ML are discussed including treatment planning, quantitative evaluation, improved visualization, early detection, and research developments. Furthermore, through the analysis of medical images, AI algorithms can detect unique characteristics of bone remodeling, predict the risk of fracture, analyze the successful outcome of treatment, and provide novel insights into the pathophysiology of disease. Interactions among health care professionals, researchers, and technologists about AI and ML in improving patients’ treatment and outcome for people with Paget's disease is crucial.

Original language	English
Title of host publication	Diagnosing Musculoskeletal Conditions using Artifical Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging
Publisher	Elsevier
Pages	105-122
Number of pages	18
ISBN (Electronic)	9780443328923
ISBN (Print)	9780443328930
DOIs	https://doi.org/10.1016/b978-0-443-32892-3.00006-3
State	Published - 1 Jan 2024
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

AIML
Bone remodeling
Diagnostic accuracy
Medical imaging
Paget's disease

Access to Document

10.1016/b978-0-443-32892-3.00006-3

Cite this

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abstract = "A chronic bone condition called Paget's disease is characterized by irregular bone restructuring that can results in fractures, deformities, and other difficulties that affect the quality of life. For effective management and treatment, early detection and accurate diagnosis are essential. The detection of Paget's disorder using medical imaging can be enhanced with the help of artificial intelligence (AI) and machine learning (ML) technology. In this work, the potential uses of AI and ML are discussed including treatment planning, quantitative evaluation, improved visualization, early detection, and research developments. Furthermore, through the analysis of medical images, AI algorithms can detect unique characteristics of bone remodeling, predict the risk of fracture, analyze the successful outcome of treatment, and provide novel insights into the pathophysiology of disease. Interactions among health care professionals, researchers, and technologists about AI and ML in improving patients{\textquoteright} treatment and outcome for people with Paget's disease is crucial.",

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Identification of paget disease in the human body using artificial intelligence and machine learning. / Sharma, Palvi; Kumar, Rakesh; Gupta, Meenu.
Diagnosing Musculoskeletal Conditions using Artifical Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging. Elsevier, 2024. p. 105-122.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Kumar, Rakesh

AU - Gupta, Meenu

PY - 2024/1/1

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AB - A chronic bone condition called Paget's disease is characterized by irregular bone restructuring that can results in fractures, deformities, and other difficulties that affect the quality of life. For effective management and treatment, early detection and accurate diagnosis are essential. The detection of Paget's disorder using medical imaging can be enhanced with the help of artificial intelligence (AI) and machine learning (ML) technology. In this work, the potential uses of AI and ML are discussed including treatment planning, quantitative evaluation, improved visualization, early detection, and research developments. Furthermore, through the analysis of medical images, AI algorithms can detect unique characteristics of bone remodeling, predict the risk of fracture, analyze the successful outcome of treatment, and provide novel insights into the pathophysiology of disease. Interactions among health care professionals, researchers, and technologists about AI and ML in improving patients’ treatment and outcome for people with Paget's disease is crucial.

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KW - Medical imaging

KW - Paget's disease

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Identification of paget disease in the human body using artificial intelligence and machine learning

Abstract

Bibliographical note

UN SDGs

Keywords

Access to Document

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