AIMC Topic: Middle Aged

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Application of deep learning for detection of nasal bone fracture on X-ray nasal bone lateral view.

Dento maxillo facial radiology
OBJECTIVES: This study aimed to assess the efficacy of deep learning applications for the detection of nasal bone fracture on X-ray nasal bone lateral view.

Pseudotargeted metabolomics profiles potential damage-associated molecular patterns as machine learning predictors for acute pancreatitis.

Journal of pharmaceutical and biomedical analysis
Acute pancreatitis (AP) is a common gastrointestinal disease characterized by pancreatic cell damage and inflammation. Given the early clinical diagnosis and management challenges, exploring novel analytical frameworks from new orientations for inter...

Quantitative Computed Tomography Measures of Lung Fibrosis and Outcomes in the National Lung Screening Trial.

Annals of the American Thoracic Society
Incidental features of interstitial lung disease (ILD) are commonly observed on chest computed tomography (CT) scans and are independently associated with poor outcomes. Although most studies to date have relied on qualitative assessments of ILD, qu...

Computer vision and tactile glove: A multimodal model in lifting task risk assessment.

Applied ergonomics
Work-related injuries from overexertion, particularly lifting, are a major concern in occupational safety. Traditional assessment tools, such as the Revised NIOSH Lifting Equation (RNLE), require significant training and practice for deployment. This...

Oscillometry-defined Small Airway Dysfunction in Tobacco-exposed Adults with Impaired or Preserved Airflow.

American journal of respiratory and critical care medicine
Small airway dysfunction (SAD) is a key feature of chronic obstructive pulmonary disease and might present in tobacco-exposed adults with normal spirometry. So far, the role of oscillometry-defined SAD in this population is largely unexplored. To i...

GPT4LFS (generative pretrained transformer 4 omni for lumbar foramina stenosis): enhancing lumbar foraminal stenosis image classification through large multimodal models.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Lumbar foraminal stenosis (LFS) is a common spinal condition that requires accurate assessment. Current magnetic resonance imaging (MRI) reporting processes are often inefficient, and while deep learning has potential for improvem...

Assessing the accuracy of the GPT-4 model in multidisciplinary tumor board decision prediction.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Artificial intelligence models like GPT-4 (OpenAI) have the potential to support clinical decision-making in oncology. This study aimed to assess the consistency between multidisciplinary tumor board (MTB) decisions and GPT-4 model predictio...

Patient perceptions of artificial intelligence in dental imaging diagnostics: a multicentre survey.

Dento maxillo facial radiology
OBJECTIVES: To evaluate patients' perceptions of the use of artificial intelligence (AI) in dental imaging diagnostics across 6 centres worldwide, hereby named according to their respective cities: Ribeirão Preto (Brazil), Aarhus (Denmark), Lyon (Fra...

Evaluating the reliability of the responses of large language models to keratoconus-related questions.

Clinical & experimental optometry
CLINICAL RELEVANCE: Artificial intelligence has undergone a rapid evolution and large language models (LLMs) have become promising tools for healthcare, with the ability of providing human-like responses to questions. The capabilities of these tools ...

[Comparison of diagnostic performance between artificial intelligence-assisted automated breast ultrasound and handheld ultrasound in breast cancer screening].

Zhonghua yi xue za zhi
To compare the diagnostic performance of artificial intelligence-assisted automated breast ultrasound (AI-ABUS) with traditional handheld ultrasound (HHUS) in breast cancer screening. A total of 36 171 women undergoing breast cancer ultrasound scre...