AIMC Topic: Deep Learning

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Community-based mosquito surveillance: an automatic mosquito-on-human-skin recognition system with a deep learning algorithm.

Pest management science
BACKGROUND: Public community engagement is crucial for mosquito surveillance programs. To support community participation, one of the approaches is assisting the public in recognizing the mosquitoes that carry pathogens. Therefore, this study aims to...

Bone visualization of the cervical spine with deep learning-based synthetic CT compared to conventional CT: A single-center noninferiority study on image quality.

European journal of radiology
PURPOSE: To investigate whether the image quality of a specific deep learning-based synthetic CT (sCT) of the cervical spine is noninferior to conventional CT.

Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images.

Medical image analysis
Since segmentation labeling is usually time-consuming and annotating medical images requires professional expertise, it is laborious to obtain a large-scale, high-quality annotated segmentation dataset. We propose a novel weakly- and semi-supervised ...

Deep learning with weak annotation from diagnosis reports for detection of multiple head disorders: a prospective, multicentre study.

The Lancet. Digital health
BACKGROUND: A large training dataset with high-quality annotations is necessary for building an accurate and generalisable deep learning system, which can be difficult and expensive to prepare in medical applications. We present a novel deep-learning...

Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation.

Journal of chemical information and modeling
Creating a wide range of new compounds that not only have ideal pharmacological properties but also easily pass long-term toxicity evaluation is still a challenging task in current drug discovery. In this study, we developed a conditional generative ...

Open Source Assessment of Deep Learning Visual Object Detection.

Sensors (Basel, Switzerland)
This paper introduces Detection Metrics, an open-source scientific software for the assessment of deep learning neural network models for visual object detection. This software provides objective performance metrics such as mean average precision and...

Research on Cyanobacterial-Bloom Detection Based on Multispectral Imaging and Deep-Learning Method.

Sensors (Basel, Switzerland)
Frequent outbreaks of cyanobacterial blooms have become one of the most challenging water ecosystem issues and a critical concern in environmental protection. To overcome the poor stability of traditional detection algorithms, this paper proposes a m...

FLED-Block: Federated Learning Ensembled Deep Learning Blockchain Model for COVID-19 Prediction.

Frontiers in public health
With the SARS-CoV-2's exponential growth, intelligent and constructive practice is required to diagnose the COVID-19. The rapid spread of the virus and the shortage of reliable testing models are considered major issues in detecting COVID-19. This pr...

Influences of Magnetic Resonance Imaging Superresolution Algorithm-Based Transition Care on Prognosis of Children with Severe Viral Encephalitis.

Computational and mathematical methods in medicine
OBJECTIVE: Its goal was to see how convolutional neural network- (CNN-) based superresolution (SR) technology magnetic resonance imaging- (MRI-) assisted transition care (TC) affected the prognosis of children with severe viral encephalitis (SVE) and...

EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review.

Computational intelligence and neuroscience
Epileptic seizure is one of the most chronic neurological diseases that instantaneously disrupts the lifestyle of affected individuals. Toward developing novel and efficient technology for epileptic seizure management, recent diagnostic approaches ha...