AIMC Topic: Deep Learning

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A Multiparametric Fusion Deep Learning Model Based on DCE-MRI for Preoperative Prediction of Microvascular Invasion in Intrahepatic Cholangiocarcinoma.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Assessment of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) by using a noninvasive method is an unresolved issue. Deep learning (DL) methods based on multiparametric fusion of MR images have the potential of preope...

Evaluation of a deep learning method for the automated detection of supraspinatus tears on MRI.

Skeletal radiology
OBJECTIVE: To evaluate if deep learning is a feasible approach for automated detection of supraspinatus tears on MRI.

Predicting adverse cardiac events in sarcoidosis: deep learning from automated characterization of regional myocardial remodeling.

The international journal of cardiovascular imaging
Recognizing early cardiac sarcoidosis (CS) imaging phenotypes can help identify opportunities for effective treatment before irreversible myocardial pathology occurs. We aimed to characterize regional CS myocardial remodeling features correlating wit...

Enhancing deep learning based classifiers with inpainting anatomical side markers (L/R markers) for multi-center trials.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The protocol for placing anatomical side markers (L/R markers) in chest radiographs varies from one hospital or department to another. However, the markers have strong signals that can be useful for deep learning-based class...

Deep Learning-Based Classification of Hepatocellular Nodular Lesions on Whole-Slide Histopathologic Images.

Gastroenterology
BACKGROUND & AIMS: Hepatocellular nodular lesions (HNLs) constitute a heterogeneous group of disorders. Differential diagnosis among these lesions, especially high-grade dysplastic nodules (HGDNs) and well-differentiated hepatocellular carcinoma (WD-...

Vulture-Based AdaBoost-Feedforward Neural Frame Work for COVID-19 Prediction and Severity Analysis System.

Interdisciplinary sciences, computational life sciences
In today's scenario, many scientists and medical researchers have been involved in deep research for discovering the desired medicine to reduce the spread of COVID-19 disease. However, still, it is not the end. Hence, predicting the COVID possibility...

DLPacker: Deep learning for prediction of amino acid side chain conformations in proteins.

Proteins
Prediction of side chain conformations of amino acids in proteins (also termed "packing") is an important and challenging part of protein structure prediction with many interesting applications in protein design. A variety of methods for packing have...

Deep Learning-based detection of psychiatric attributes from German mental health records.

International journal of medical informatics
BACKGROUND: Health care records provide large amounts of data with real-world and longitudinal aspects, which is advantageous for predictive analyses and improvements in personalized medicine. Text-based records are a main source of information in me...

A deep learning system for automated kidney stone detection and volumetric segmentation on noncontrast CT scans.

Medical physics
PURPOSE: Early detection and size quantification of renal calculi are important for optimizing treatment and preventing severe kidney stone disease. Prior work has shown that volumetric measurements of kidney stones are more informative and reproduci...

Research on Small Sample Dynamic Human Ear Recognition Based on Deep Learning.

Sensors (Basel, Switzerland)
Due to the problem of insufficient dynamic human ear data, the Changchun University dynamic human ear (CCU-DE) database, which is a small sample human ear database, was developed in this study. The database fully considers the various complex situati...