AIMC Topic: Deep Learning

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Accuracy of large language models in answering ophthalmology board-style questions: A meta-analysis.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To evaluate the accuracy of large language models (LLMs) in answering ophthalmology board-style questions.

Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound.

Asian journal of andrology
Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) ...

Coronary artery disease detection using deep learning and ultrahigh-resolution photon-counting coronary CT angiography.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate the diagnostic performance of automated deep learning in the detection of coronary artery disease (CAD) on photon-counting coronary CT angiography (PC-CCTA).

A unified multimodal classification framework based on deep metric learning.

Neural networks : the official journal of the International Neural Network Society
Multimodal classification algorithms play an essential role in multimodal machine learning, aiming to categorize distinct data points by analyzing data characteristics from multiple modalities. Extensive research has been conducted on distilling mult...

A novel mean shape based post-processing method for enhancing deep learning lower-limb muscle segmentation accuracy.

PloS one
This study aims at improving the lower-limb muscle segmentation accuracy of deep learning approaches based on Magnetic Resonance Imaging (MRI) scans, crucial for the diagnostic and therapeutic processes in musculoskeletal diseases. In general, segmen...

A deep learning approach to case prioritisation of colorectal biopsies.

Histopathology
AIMS: To create and validate a weakly supervised artificial intelligence (AI) model for detection of abnormal colorectal histology, including dysplasia and cancer, and prioritise biopsies according to clinical significance (severity of diagnosis).

ECG classification based on guided attention mechanism.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Integrating domain knowledge into deep learning models can improve their effectiveness and increase explainability. This study aims to enhance the classification performance of electrocardiograms (ECGs) by customizing specif...

Automated deep learning segmentation of cardiac inflammatory FDG PET.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Fluorodeoxyglucose positron emission tomography (FDG PET) with suppression of myocardial glucose utilization plays a pivotal role in diagnosing cardiac sarcoidosis. Reorientation of images to match perfusion datasets and myocardial segmen...

Two-stage deep learning framework for occlusal crown depth image generation.

Computers in biology and medicine
The generation of depth images of occlusal dental crowns is complicated by the need for customization in each case. To decrease the workload of skilled dental technicians, various computer vision models have been used to generate realistic occlusal c...

Deep learning predicted perceived age is a reliable approach for analysis of facial ageing: A proof of principle study.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Perceived age (PA) has been associated with mortality, genetic variants linked to ageing and several age-related morbidities. However, estimating PA in large datasets is laborious and costly to generate, limiting its practical applicabili...