AIMC Topic: Predictive Value of Tests
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The TabNet Model for Diagnosing Axial Spondyloarthritis Using MRI Imaging Findings and Clinical Risk Factors.
International journal of rheumatic diseases
Dec 1, 2024
OBJECTIVES: The aim of this study is to develop and validate a model for predicting axial spondyloarthritis (axSpA) based on sacroiliac joint (SIJ)-MRI imaging findings and clinical risk factors.
Diffusion-weighted MRI precisely predicts telomerase reverse transcriptase promoter mutation status in World Health Organization grade IV gliomas using a residual convolutional neural network.
The British journal of radiology
Nov 1, 2024
OBJECTIVES: Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with World Health Organization (WHO) grade IV glioma. This study was conducted to assess the valu...
Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors.
World journal of gastroenterology
Oct 28, 2024
BACKGROUND: Although immune checkpoint inhibitors (ICIs) have demonstrated significant survival benefits in some patients diagnosed with gastric cancer (GC), existing prognostic markers are not universally applicable to all patients with advanced GC.
Review on article of preoperative prediction in chronic hepatitis B virus patients using spectral computed tomography and machine learning.
World journal of gastroenterology
Oct 14, 2024
This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately. We ...
Prediction of Glioma enhancement pattern using a MRI radiomics-based model.
Medicine
Sep 6, 2024
Contrast-MRI scans carry risks associated with the chemical contrast agents. Accurate prediction of enhancement pattern of gliomas has potential in avoiding contrast agent administration to patients. This study aimed to develop a machine learning rad...
Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules.
JNCI cancer spectrum
Sep 2, 2024
BACKGROUND: Clinical utility data on pulmonary nodule (PN) risk stratification biomarkers are lacking. We aimed to determine the incremental predictive value and clinical utility of using an artificial intelligence (AI) radiomics-based computer-aided...
Sequential Prediction of Interstitial Lung Abnormalities Using Machine Learning.
Radiology
Sep 1, 2024
Predicting lymph node recurrence in cT1-2N0 tongue squamous cell carcinoma: collaboration between artificial intelligence and pathologists.
The journal of pathology. Clinical research
Sep 1, 2024
Researchers have attempted to identify the factors involved in lymph node recurrence in cT1-2N0 tongue squamous cell carcinoma (SCC). However, studies combining histopathological and clinicopathological information in prediction models are limited. W...
Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).
Radiology. Artificial intelligence
Sep 1, 2024
Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy using MRI and basic clinical data. Materials and Methods In this study, MRI data of term neonates with encepha...
Presurgical Upgrade Prediction of DCIS to Invasive Ductal Carcinoma Using Time-dependent Deep Learning Models with DCE MRI.
Radiology. Artificial intelligence
Sep 1, 2024
Purpose To determine whether time-dependent deep learning models can outperform single time point models in predicting preoperative upgrade of ductal carcinoma in situ (DCIS) to invasive malignancy at dynamic contrast-enhanced (DCE) breast MRI withou...
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