AIMC Topic: Deep Learning

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Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.

European radiology
OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk.

Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed ...

Deep Learning-Based Automated Labeling of Coronary Segments for Structured Reporting of Coronary Computed Tomography Angiography in Accordance With Society of Cardiovascular Computed Tomography Guidelines.

Journal of thoracic imaging
PURPOSE: To evaluate a novel deep learning (DL)-based automated coronary labeling approach for structured reporting of coronary artery disease according to the guidelines of the Society of Cardiovascular Computed Tomography (CT) on coronary CT angiog...

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features.

The journal of pathology. Clinical research
Liver is one of the most common sites for metastases, which can occur on account of primary tumors from multiple sites of origin. Identifying the primary site of origin (PSO) of a metastasis can help in guiding therapeutic options for liver metastase...

DeepDRP: Prediction of intrinsically disordered regions based on integrated view deep learning architecture from transformer-enhanced and protein information.

International journal of biological macromolecules
Intrinsic disorder in proteins, a widely distributed phenomenon in nature, is related to many crucial biological processes and various diseases. Traditional determination methods tend to be costly and labor-intensive, therefore it is desirable to see...

Integrating street view images and deep learning to explore the association between human perceptions of the built environment and cardiovascular disease in older adults.

Social science & medicine (1982)
Understanding how built environment attributes affect health remains important. While many studies have explored the objective characteristics of built environments that affect health outcomes, few have examined the role of human perceptions of built...

ResBiGAAT: Residual Bi-GRU with attention for protein-ligand binding affinity prediction.

Computational biology and chemistry
Protein-ligand interaction plays a crucial role in drug discovery, facilitating efficient drug development and enabling drug repurposing. Several computational algorithms, such as Graph Neural Networks and Convolutional Neural Networks, have been pro...

Performance of deep learning models for response evaluation on whole-body bone scans in prostate cancer.

Annals of nuclear medicine
OBJECTIVE: We aimed to develop deep learning classifiers for assessing therapeutic response on bone scans of patients with prostate cancer.

Direct deep learning-based survival prediction from pre-interventional CT prior to transcatheter aortic valve replacement.

European journal of radiology
PURPOSE: To investigate survival prediction in patients undergoing transcatheter aortic valve replacement (TAVR) using deep learning (DL) methods applied directly to pre-interventional CT images and to compare performance with survival models based o...

Optimal view detection for ultrasound-guided supraclavicular block using deep learning approaches.

Scientific reports
Successful ultrasound-guided supraclavicular block (SCB) requires the understanding of sonoanatomy and identification of the optimal view. Segmentation using a convolutional neural network (CNN) is limited in clearly determining the optimal view. The...