AIMC Topic: Deep Learning

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Deep learning accurately classifies elbow joint effusion in adult and pediatric radiographs.

Scientific reports
Joint effusion due to elbow fractures are common among adults and children. Radiography is the most commonly used imaging procedure to diagnose elbow injuries. The purpose of the study was to investigate the diagnostic accuracy of deep convolutional ...

Feasibility study of three-material decomposition in dual-energy cone-beam CT imaging with deep learning.

Physics in medicine and biology
In this work, a dedicated end-to-end deep convolutional neural network, named as Triple-CBCT, is proposed to demonstrate the feasibility of reconstructing three different material distribution volumes from the dual-energy CBCT projection data.In Trip...

Cultural and Creative Product Design and Image Recognition Based on Deep Learning.

Computational intelligence and neuroscience
In today's technological world, advanced intelligence technologies such as deep learning (DL) techniques are widely applied in various fields. In this study, people are going to research cultural and creative product design and image recognition base...

Teachers' Teaching Ability Promotion Strategies Based on Lightweight Deep Learning Combined with Target Detection Algorithm.

Computational intelligence and neuroscience
With the popularization of standardized classrooms in colleges and universities, it is possible to collect video data of students' class status through the camera device in the classroom. With abundant video data sources, it is easy to obtain big dat...

Deep Learning-Based Football Player Detection in Videos.

Computational intelligence and neuroscience
The main task of football video analysis is to detect and track players. In this work, we propose a deep convolutional neural network-based football video analysis algorithm. This algorithm aims to detect the football player in real time. First, five...

Development and Validation of a Deep Learning System for Sound-based Prediction of Urinary Flow.

European urology focus
BACKGROUND: Uroflowmetry remains an important tool for the assessment of patients with lower urinary tract symptoms (LUTS), but accuracy can be limited by within-subject variation of urinary flow rates. Voiding acoustics appear to correlate well with...

A novel end-to-end deep learning solution for coronary artery segmentation from CCTA.

Medical physics
PURPOSE: Coronary computed tomographic angiography (CCTA) plays a vital role in the diagnosis of cardiovascular diseases, among which automatic coronary artery segmentation (CAS) serves as one of the most challenging tasks. To computationally assist ...

Intuitive physics learning in a deep-learning model inspired by developmental psychology.

Nature human behaviour
'Intuitive physics' enables our pragmatic engagement with the physical world and forms a key component of 'common sense' aspects of thought. Current artificial intelligence systems pale in their understanding of intuitive physics, in comparison to ev...

A deep learning approach for Spatio-Temporal forecasting of new cases and new hospital admissions of COVID-19 spread in Reggio Emilia, Northern Italy.

Journal of biomedical informatics
BACKGROUND: Since February 2020, the COVID-19 epidemic has rapidly spread throughout Italy. Some studies showed an association of environmental factors, such as PM, PM NO, temperature, relative humidity, wind speed, solar radiation and mobility with ...

Deep-learning-based classification of desmoplastic reaction on H&E predicts poor prognosis in oesophageal squamous cell carcinoma.

Histopathology
AIMS: Desmoplastic reaction (DR) categorisation has been shown to be a promising prognostic factor in oesophageal squamous cell carcinoma (ESCC). The usual DR evaluation is performed using semiquantitative scores, which can be subjective. This study ...