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A Framework on A Computer Assisted and Systematic Methodology for Detection of Chronic Lower Back Pain using Artificial Intelligence and Computer Graphics Technologies

Al Kafri, A and Sudirman, S and Hussain, A and Fergus, P and Al-Jumeily, D and Al-Jumaily, M and Alaskar, H (2016) A Framework on A Computer Assisted and Systematic Methodology for Detection of Chronic Lower Back Pain using Artificial Intelligence and Computer Graphics Technologies. In: Intelligent Computing Theories and Application: Lecture Notes in Computer Science , 9771. pp. 843-854. (2016 International Conference on Intelligent Computation, 02 August 2016 - 05 August 2016, Lanzhou,China).

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Abstract

Back pain is one of the major musculoskeletal pain problems that can affect many people and is considered as one of the main causes of disability all over the world. Lower back pain, which is the most common type of back pain, is estimated to affect at least 60% to 80% of the adult population in the United Kingdom at some time in their lives. Some of those patients develop a more serious condition namely Chronic Lower Back Pain in which physicians must carry out a more involved diagnostic procedure to determine its cause. In most cases, this procedure involves a long and laborious task by the physicians to visually identify abnormalities from the patient’s Magnetic Resonance Images. Limited technological advances have been made in the past decades to support this process. This paper presents a comprehensive literature review on these technological advances and presents a framework of a methodology for diagnosing and predicting Chronic Lower Back Pain. This framework will combine current state-of-the-art computing technologies including those in the area of artificial intelligence, physics modelling, and computer graphics, and is argued to be able to improve the diagnosis process.

Item Type: Conference or Workshop Item (Paper)
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-42291-6_83
Uncontrolled Keywords: 08 Information And Computing Sciences
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science
Publisher: Springer Verlag (Germany)
Date Deposited: 16 Dec 2016 12:20
Last Modified: 16 Dec 2016 12:28
URI: http://researchonline.ljmu.ac.uk/id/eprint/3536

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