AIMC Topic: Deep Learning

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A deep learning framework for automated detection and quantitative assessment of liver trauma.

BMC medical imaging
BACKGROUND: Both early detection and severity assessment of liver trauma are critical for optimal triage and management of trauma patients. Current trauma protocols utilize computed tomography (CT) assessment of injuries in a subjective and qualitati...

Optimization of a Deep Learning Algorithm for Security Protection of Big Data from Video Images.

Computational intelligence and neuroscience
With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems. Aiming at preventing privacy dis...

Deep Learning in Healthcare System for Quality of Service.

Journal of healthcare engineering
Deep learning (DL) and machine learning (ML) have a pivotal role in logistic supply chain management and smart manufacturing with proven records. The ability to handle large complex data with minimal human intervention made DL and ML a success in the...

A new pairwise deep learning feature for environmental microorganism image analysis.

Environmental science and pollution research international
Environmental microorganism (EM) offers a highly efficient, harmless, and low-cost solution to environmental pollution. They are used in sanitation, monitoring, and decomposition of environmental pollutants. However, this depends on the proper identi...

Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study.

The Lancet. Digital health
BACKGROUND: Diabetic retinopathy is a leading cause of preventable blindness, especially in low-income and middle-income countries (LMICs). Deep-learning systems have the potential to enhance diabetic retinopathy screenings in these settings, yet pro...

Semi-Supervised Deep Learning Semantic Segmentation for 3D Volumetric Computed Tomographic Scoring of Chronic Rhinosinusitis: Clinical Correlations and Comparison with Lund-Mackay Scoring.

Tomography (Ann Arbor, Mich.)
BACKGROUND: The traditional Lund-Mackay score (TLMs) is unable to subgrade the volume of inflammatory disease. We aimed to propose an effective modification and calculated the volume-based modified LM score (VMLMs), which should correlate more strong...

Probabilistic Maritime Trajectory Prediction in Complex Scenarios Using Deep Learning.

Sensors (Basel, Switzerland)
Maritime activity is expected to increase, and therefore also the need for maritime surveillance and safety. Most ships are obligated to identify themselves with a transponder system like the Automatic Identification System (AIS) and ships that do no...

Artificial Intelligent Deep Learning Molecular Generative Modeling of Scaffold-Focused and Cannabinoid CB2 Target-Specific Small-Molecule Sublibraries.

Cells
Design and generation of high-quality target- and scaffold-specific small molecules is an important strategy for the discovery of unique and potent bioactive drug molecules. To achieve this goal, authors have developed the deep-learning molecule gene...

Determining the anatomical site in knee radiographs using deep learning.

Scientific reports
An important quality criterion for radiographs is the correct anatomical side marking. A deep neural network is evaluated to predict the correct anatomical side in radiographs of the knee acquired in anterior-posterior direction. In this retrospectiv...

Generalization of Deep Learning Gesture Classification in Robotic-Assisted Surgical Data: From Dry Lab to Clinical-Like Data.

IEEE journal of biomedical and health informatics
OBJECTIVE: Robotic-assisted minimally invasive surgery (RAMIS) became a common practice in modern medicine and is widely studied. Surgical procedures require prolonged and complex movements; therefore, classifying surgical gestures could be helpful t...