The Cervical Spine

Daniels, J. M.; Kary, Joel M.

doi:10.1007/978-1-4419-5523-4_2

Common Musculoskeletal Problems 2010

DOI: 10.1007/978-1-4419-5523-4_2

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The Cervical Spine

J. M. Daniels

Joel M. Kary²

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Cited by 4 publications

(1 citation statement)

References 12 publications

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“…Mechanical neck pain (MNP) is a general term for a vague discomfort that intensifies with neck movement (Daniels and Kary., 2011). Neck pain was classified as "non-specific" or mechanical when it was induced or aggravated by neck motions or chronic neck postures, and no specific underlying condition could be found (Ferrari et al,2003).…”

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confidence: 99%

The impact of mechanical neck pain on peak expiratory flow in smartphone addicted population.

Ghaly¹

2022

Delta University Scientific Journal

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Background: Mechanical neck pain seen in smartphone addicted population causes respiratory hazards and decrease in peak expiratory flow. Aim: To detect the effect of mechanical neck pain on peak expiratory flow in smartphone addicted population. Methods: 100 volunteers of smartphone addicts with mechanical neck pain were recruited from delta university for science and technology. Their age ranged from 18-25 years. Both sexes were included (47 males, 53 females). Their peak expiratory flow (PEF) was measured using spirometer and the results were compared to the normal predicted values based on age, sex, race, weight and height. Results: there was a significant decrease (P<0.05) in PEF in smartphone addicts with mechanical neck pain compared to normal predicted values. Conclusion: Mechanical neck pain causes decrease in PEF in smartphone addicted population.

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confidence: 99%

The impact of mechanical neck pain on peak expiratory flow in smartphone addicted population.

Ghaly¹

2022

Delta University Scientific Journal

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The effectiveness of Q6 and PIPER 6-year-old models on quantification of the change of child sitting posture with AEB and its impact on child’s injures in frontal crash

Zhang,

Feng,

Xue

et al. 2024

Traffic Injury Prevention

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Classification of Cervical Spine Fracture and Dislocation Using Refined Pre-Trained Deep Model and Saliency Map

et al. 2023

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Cervical spine (CS) fractures or dislocations are medical emergencies that may lead to more serious consequences, such as significant functional disability, permanent paralysis, or even death. Therefore, diagnosing CS injuries should be conducted urgently without any delay. This paper proposes an accurate computer-aided-diagnosis system based on deep learning (AlexNet and GoogleNet) for classifying CS injuries as fractures or dislocations. The proposed system aims to support physicians in diagnosing CS injuries, especially in emergency services. We trained the model on a dataset containing 2009 X-ray images (530 CS dislocation, 772 CS fractures, and 707 normal images). The results show 99.56%, 99.33%, 99.67%, and 99.33% for accuracy, sensitivity, specificity, and precision, respectively. Finally, the saliency map has been used to measure the spatial support of a specific class inside an image. This work targets both research and clinical purposes. The designed software could be installed on the imaging devices where the CS images are captured. Then, the captured CS image is used as an input image where the designed code makes a clinical decision in emergencies.

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The Cervical Spine

Cited by 4 publications

References 12 publications

The impact of mechanical neck pain on peak expiratory flow in smartphone addicted population.

The impact of mechanical neck pain on peak expiratory flow in smartphone addicted population.

The effectiveness of Q6 and PIPER 6-year-old models on quantification of the change of child sitting posture with AEB and its impact on child’s injures in frontal crash

Classification of Cervical Spine Fracture and Dislocation Using Refined Pre-Trained Deep Model and Saliency Map

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