AIMC Topic: Deep Learning

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Riverbed litter monitoring using consumer-grade aerial-aquatic speedy scanner (AASS) and deep learning based super-resolution reconstruction and detection network.

Marine pollution bulletin
Underwater litter is widely spread across aquatic environments such as lakes, rivers, and oceans, significantly impacting natural ecosystems. Current automated monitoring technologies for detecting this litter face limitations in survey efficiency, c...

Improving tabular data extraction in scanned laboratory reports using deep learning models.

Journal of biomedical informatics
OBJECTIVE: Medical laboratory testing is essential in healthcare, providing crucial data for diagnosis and treatment. Nevertheless, patients' lab testing results are often transferred via fax across healthcare organizations and are not immediately av...

Trends in brain MRI and CP association using deep learning.

La Radiologia medica
Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functions. It may lead to an intellectual disability and affect the quality of life. Early intervention is critical and challenging due to the uncooperative...

Exploring Protein Conformational Changes Using a Large-Scale Biophysical Sampling Augmented Deep Learning Strategy.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. Currently, a major challenge in the de...

RingGesture: A Ring-Based Mid-Air Gesture Typing System Powered by a Deep-Learning Word Prediction Framework.

IEEE transactions on visualization and computer graphics
Text entry is a critical capability for any modern computing experience, with lightweight augmented reality (AR) glasses being no exception. Designed for all-day wearability, a limitation of lightweight AR glass is the restriction to the inclusion of...

InstructNet: A novel approach for multi-label instruction classification through advanced deep learning.

PloS one
People use search engines for various topics and items, from daily essentials to more aspirational and specialized objects. Therefore, search engines have taken over as people's preferred resource. The "How To" prefix has become familiar and widely u...

Deep learning from head CT scans to predict elevated intracranial pressure.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: Elevated intracranial pressure (ICP) resulting from severe head injury or stroke poses a risk of secondary brain injury that requires neurosurgical intervention. However, currently available noninvasive monitoring techniques f...

Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts.

Journal of imaging informatics in medicine
Ischemic changes are not visible on non-contrast head CT until several hours after infarction, though deep convolutional neural networks have shown promise in the detection of subtle imaging findings. This study aims to assess if dual-energy CT (DECT...

A deep drug prediction framework for viral infectious diseases using an optimizer-based ensemble of convolutional neural network: COVID-19 as a case study.

Molecular diversity
The SARS-CoV-2 outbreak highlights the persistent vulnerability of humanity to epidemics and emerging microbial threats, emphasizing the lack of time to develop disease-specific treatments. Therefore, it appears beneficial to utilize existing resourc...

Optimizing Catheter Verification: An Understandable AI Model for Efficient Assessment of Central Venous Catheter Placement in Chest Radiography.

Investigative radiology
PURPOSE: Accurate detection of central venous catheter (CVC) misplacement is crucial for patient safety and effective treatment. Existing artificial intelligence (AI) often grapple with the limitations of label inaccuracies and output interpretations...