AIMC Topic: Deep Learning

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Deep learning-based integration of genetics with registry data for stratification of schizophrenia and depression.

Science advances
Currently, psychiatric diagnoses are, in contrast to most other medical fields, based on subjective symptoms and observable signs and call for new and improved diagnostics to provide the most optimal care. On the basis of a deep learning approach, we...

Deep learning to diagnose Hashimoto's thyroiditis from sonographic images.

Nature communications
Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model called HTNet for diagnosis of HT by training on 106,513 thyroid ultrasound images from 17,934 patients and test its performance on 5051 patients from 2...

Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load.

eLife
Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of...

Automated identification of chicken distress vocalizations using deep learning models.

Journal of the Royal Society, Interface
The annual global production of chickens exceeds 25 billion birds, which are often housed in very large groups, numbering thousands. Distress calling triggered by various sources of stress has been suggested as an 'iceberg indicator' of chicken welfa...

Light-Weighted Deep Learning Model to Detect Fault in IoT-Based Industrial Equipment.

Computational intelligence and neuroscience
Industry 4.0, with the widespread use of IoT, is a significant opportunity to improve the reliability of industrial equipment through problem detection. It is difficult to utilize a unified model to depict the working condition of devices in real-wor...

Exploring the Development of Chinese Digital Resources under Lightweight Deep Learning.

Computational intelligence and neuroscience
From 2019, countries worldwide have been negatively affected by the corona virus disease 2019 (COVID-19) in all aspects of social life. The high-tech digital industry represented by emerging digital technologies is still vigorous, and correspondingly...

Analysis of the Effect of Urban Residents' Sports Consumption on GDP Growth Based on Deep Learning.

Computational intelligence and neuroscience
Nowadays, emerging industries are emerging, and the sports industry has become a remarkable new economic growth point. Vigorously tapping the potential of residents' sports consumption has important theoretical and practical significance for promotin...

Deep Learning Approaches for Automatic Localization in Medical Images.

Computational intelligence and neuroscience
Recent revolutionary advances in deep learning (DL) have fueled several breakthrough achievements in various complicated computer vision tasks. The remarkable successes and achievements started in 2012 when deep learning neural networks (DNNs) outper...

Deep Learning and Transfer Learning for Malaria Detection.

Computational intelligence and neuroscience
Infectious disease malaria is a devastating infectious disease that claims the lives of more than 500,000 people worldwide every year. Most of these deaths occur as a result of a delayed or incorrect diagnosis. At the moment, the manual microscope is...

Intelligent Research Based on Deep Learning Recognition Method in Vehicle-Road Cooperative Information Interaction System.

Computational intelligence and neuroscience
The vehicle-road collaborative information interaction system is an emerging technology system that realizes the sharing of information between vehicles, vehicles and roads between traffic road information, and driving vehicle information. It is of p...