AIMC Topic: Middle Aged

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A deep learning tool without muscle-by-muscle grading to differentiate myositis from facio-scapulo-humeral dystrophy using MRI.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to assess the capabilities of a deep learning (DL) tool to discriminate between type 1 facioscapulo-humeral dystrophy (FSHD1) and myositis using whole-body muscle magnetic resonance imaging (MRI) examination wit...

Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma.

BMC cancer
BACKGROUND: Accurate prognosis assessment is essential for surgically resected intrahepatic cholangiocarcinoma (ICC) while published prognostic tools are limited by modest performance. We therefore aimed to establish a novel model to predict survival...

Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany.

Scientific reports
During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and interpretable forecasts of disease incidents are a vital tool for policymakers to manage healthcare resou...

Intelligent Algorithm-Based Ultrasound Image for Evaluating the Effect of Comprehensive Nursing Scheme on Patients with Diabetic Kidney Disease.

Computational and mathematical methods in medicine
This study was aimed at exploring the effect of ultrasound image evaluation of comprehensive nursing scheme based on artificial intelligence algorithms on patients with diabetic kidney disease (DKD). 44 patients diagnosed with DKD were randomly divid...

Automatic detection and classification of knee osteoarthritis using deep learning approach.

La Radiologia medica
PURPOSE: We developed a tool for locating and grading knee osteoarthritis (OA) from digital X-ray images and illustrate the possibility of deep learning techniques to predict knee OA as per the Kellgren-Lawrence (KL) grading system. The purpose of th...

Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy.

Journal of diabetes research
AIMS: To investigate the applicability of deep learning image assessment software VeriSee DR to different color fundus cameras for the screening of diabetic retinopathy (DR).

A Broad Learning System to Predict the 28-Day Mortality of Patients Hospitalized with Community-Acquired Pneumonia: A Case-Control Study.

Computational and mathematical methods in medicine
This study was to conduct a model based on the broad learning system (BLS) for predicting the 28-day mortality of patients hospitalized with community-acquired pneumonia (CAP). A total of 1,210 eligible CAP cases from Chifeng Municipal Hospital were ...

Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning.

Oxidative medicine and cellular longevity
BACKGROUND: Ovarian cancer (OC) is a malignancy exhibiting high mortality in female tumors. Glycosylation is a posttranslational modification of proteins but research has failed to demonstrate a systematic link between glycosylation-related signature...

Artificial intelligence in computed tomography for quantifying lung changes in the era of CFTR modulators.

The European respiratory journal
BACKGROUND: Chest computed tomography (CT) remains the imaging standard for demonstrating cystic fibrosis (CF) airway structural disease . However, visual scoring systems as an outcome measure are time consuming, require training and lack high reprod...

Prediction of pouchitis after ileal pouch-anal anastomosis in patients with ulcerative colitis using artificial intelligence and deep learning.

Techniques in coloproctology
BACKGROUND: Pouchitis is one of the major postoperative complications of ulcerative colitis (UC), and it is still difficult to predict the development of pouchitis after ileal pouch-anal anastomosis (IPAA) in UC patients. In this study, we examined w...