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Automated diagnosis and classification of metacarpal and phalangeal fractures using a convolutional neural network: a retrospective data analysis study.

Acta Orthop

January 2025

Department of Orthopaedic Surgery, Danderyd Hospital, Stockholm; 2 Department of Clinical Sciences at Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden.

Background And Purpose:  Hand fractures are commonly presented in emergency departments, yet diagnostic errors persist, leading to potential complications. The use of artificial intelligence (AI) in fracture detection has shown promise, but research focusing on hand metacarpal and phalangeal fractures remains limited. We aimed to train and evaluate a convolutional neural network (CNN) model to diagnose metacarpal and phalangeal fractures using plain radiographs according to the AO/OTA classification system and custom classifiers.

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Article Synopsis
  • The study investigates using artificial intelligence, specifically deep learning models (DLMs), to accurately identify radiographic landmarks before and after shoulder arthroplasty, which is typically a tedious manual process.
  • A total of 240 anteroposterior radiographs were annotated, creating a dataset that trained the DLM to achieve a mean deviation of only 1.9 mm when comparing DLM-identified landmarks to those identified by surgeons.
  • The DLM demonstrated promise in efficiently analyzing radiographs with minimal human error, suggesting it could significantly aid in the evaluation of shoulder surgeries while also improving the reliability of measurements related to glenohumeral relationships.
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Axial Spondyloarthritis (SpA) is a chronic inflammatory disease of the spine associated with the gene HLA-B27. Non-radiographic spondyloarthritis (nr-SpA), an early stage of axial SpA often goes unrecognized in many settings including the Philippines. We describe five Filipinos from a tertiary health care facility who fulfill the Assessment of SpondyloArthritis International Society (ASAS) 2009 criteria for non-radiographic SpA with the aim of increasing awareness of this disease in the Philippines.

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Background: The Australian Rheumatology Association identified the use of imaging in patients with low back pain without indication of serious pathology as a low-value practice.

Aims: To determine the appropriateness of diagnostic lumbar spine imaging requests in patients with low back pain presenting to a Western Australian hospital's emergency department.

Methods: We conducted a retrospective review of all adult patients (18 years and older) who presented with low back pain to the Fiona Stanley Hospital emergency department from 1 July 2020 to 31 December 2020.

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Combat sports encompass a wide range of disciplines, each associated with distinct injury patterns and mechanisms. From karate to wrestling, athletes face varying degrees of injury risks, with common clinical presentations including head injuries, strains, sprains, fractures, and concussions. These injuries often result from dynamic movements, physical contact, and high-impact collisions inherent to combat sports.

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