Authors’ Response

Navallas, María; Ares, Jesús; Beltrán, Brigitte; Solano, A.; Maymó, Joan

doi:10.1148/radiographics.33.4.334959

Cited by 1 publication

(1 citation statement)

References 21 publications

(20 reference statements)

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“…When these radiological changes manifest, AS, a radiographic AxSpA, can be diagnosed. Despite the perception, it is easy to diagnose radiographic AxSpA compared to non-radiographic AxSpA [6], and the disease typically progresses slowly before the occurrence of the symptoms on a conventional radiography. Because, at present there are no direct diagnostics that may reliably identify early stage signs of AS, medical imaging is employed to make the diagnosis [7].…”

Section: Introductionmentioning

confidence: 99%

An Overview of Inflammatory Spondylitis for Biomedical Imaging Using Deep Neural Networks

Kokkula Shiva Prasad

2023

IJRITCC

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Ankylosing Spondylitis (AS) is an axial spine inflammatory illness and also chronic that might present with a range of clinical symptoms and indicators. The illness is most frequently characterized by increasing spinal stiffness and persistent back discomfort. The affect of the sacroiliac joints, spine, peripheral joints, entheses and digits are the main cause of the illness. AS symptoms include reduced spinal mobility, aberrant posture, hip and dactylitis, enthesitis, peripheral arthritis, and buttock pain. With their exceptional picture classification ability, the diagnosis of AS illness has been transformed by deep learning techniques in artificial intelligence (AI). Despite the excellent results, these processes are still being widely used in clinical practice at a moderate rate. Due to security and health concerns, medical imaging applications utilizing deep learning must be viewed with caution. False instances, whether good or negative, have far-reaching effects on the well-being of patients and these are to be considered. These are extracted from the fact of the state-of-the-art of deep learning (DL) algorithms lack internal workings comprehension and have complicated interconnected structure, huge millions of parameters, and also a "black box" aspect compared to conventional machine learning (ML) algorithms. XAI (Explainable AI) approaches make it easier to comprehend model predictions, which promotes system reliability, speeds up the diagnosis of the AS disease, and complies with legal requirements.

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Section: Introductionmentioning

confidence: 99%

An Overview of Inflammatory Spondylitis for Biomedical Imaging Using Deep Neural Networks

Kokkula Shiva Prasad

2023

IJRITCC

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Authors’ Response

Cited by 1 publication

References 21 publications

An Overview of Inflammatory Spondylitis for Biomedical Imaging Using Deep Neural Networks

An Overview of Inflammatory Spondylitis for Biomedical Imaging Using Deep Neural Networks

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