AIMC Topic: Cross-Sectional Studies
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Network analysis of trauma in patients with early-stage psychosis.
Scientific reports
Nov 23, 2021
Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are common in psychosis. The present study aimed to perform a network analysis of interactions between ...
Effect of data leakage in brain MRI classification using 2D convolutional neural networks.
Scientific reports
Nov 19, 2021
In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high perform...
Alzheimer Disease
Image Interpretation, Computer-Assisted
Neuroimaging
Humans
Male
Parkinson Disease
Reproducibility of Results
Middle Aged
Deep Learning
Neural Networks, Computer
Aged, 80 and over
Predictive Value of Tests
Aged
Case-Control Studies
Brain
Magnetic Resonance Imaging
Female
Cross-Sectional Studies
Automated Whole-Liver MRI Segmentation to Assess Steatosis and Iron Quantification in Chronic Liver Disease.
Radiology
Nov 16, 2021
Background Standardized manual region of interest (ROI) sampling strategies for hepatic MRI steatosis and iron quantification are time consuming, with variable results. Purpose To evaluate the performance of automatic MRI whole-liver segmentation (WL...
Accurate Identification of the Trabecular Meshwork under Gonioscopic View in Real Time Using Deep Learning.
Ophthalmology. Glaucoma
Nov 16, 2021
PURPOSE: Accurate identification of iridocorneal structures on gonioscopy is difficult to master, and errors can lead to grave surgical complications. This study aimed to develop and train convolutional neural networks (CNNs) to accurately identify t...
Fully automated deep learning for knee alignment assessment in lower extremity radiographs: a cross-sectional diagnostic study.
Skeletal radiology
Nov 13, 2021
OBJECTIVES: Accurate assessment of knee alignment and leg length discrepancy is currently measured manually from standing long-leg radiographs (LLR), a process that is both time consuming and poorly reproducible. The aim was to assess the performance...
A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.
Nutrients
Nov 10, 2021
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...
Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study.
Frontiers in public health
Nov 5, 2021
What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks? Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decade...
Building a predictive model to assist in the diagnosis of cervical cancer.
Future oncology (London, England)
Nov 3, 2021
Cervical cancer is still one of the most common gynecologic cancers in the world. Since cervical cancer is a potentially preventive cancer, earlier detection is the most effective technique for decreasing the worldwide incidence of the illness. Thi...
Natural Language Processing and Machine Learning Methods to Characterize Unstructured Patient-Reported Outcomes: Validation Study.
Journal of medical Internet research
Nov 3, 2021
BACKGROUND: Assessing patient-reported outcomes (PROs) through interviews or conversations during clinical encounters provides insightful information about survivorship.
The Impact of Explanations on Layperson Trust in Artificial Intelligence-Driven Symptom Checker Apps: Experimental Study.
Journal of medical Internet research
Nov 3, 2021
BACKGROUND: Artificial intelligence (AI)-driven symptom checkers are available to millions of users globally and are advocated as a tool to deliver health care more efficiently. To achieve the promoted benefits of a symptom checker, laypeople must tr...
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