AIMC Topic: Deep Learning

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Deep-Learning-Based ADHD Classification Using Children's Skeleton Data Acquired through the ADHD Screening Game.

Sensors (Basel, Switzerland)
The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for early diagnosis and treatment. However, since ADHD is not a simple disease that can be diagnosed with a...

Traditional Machine and Deep Learning for Predicting Toxicity Endpoints.

Molecules (Basel, Switzerland)
Molecular structure property modeling is an increasingly important tool for predicting compounds with desired properties due to the expensive and resource-intensive nature and the problem of toxicity-related attrition in late phases during drug disco...

A Novel Groundwater Burial Depth Prediction Model Based on Two-Stage Modal Decomposition and Deep Learning.

International journal of environmental research and public health
The variability of groundwater burial depths is critical to regional water management. In order to reduce the impact of high-frequency eigenmodal functions (IMF) generated by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN...

Automated quantitative assessment of pediatric blunt hepatic trauma by deep learning-based CT volumetry.

European journal of medical research
BACKGROUND: To develop an end-to-end deep learning method for automated quantitative assessment of pediatric blunt hepatic trauma based on contrast-enhanced computed tomography (CT).

Physical deep learning with biologically inspired training method: gradient-free approach for physical hardware.

Nature communications
Ever-growing demand for artificial intelligence has motivated research on unconventional computation based on physical devices. While such computation devices mimic brain-inspired analog information processing, the learning procedures still rely on m...

Intraoperative cytological diagnosis of brain tumours: A preliminary study using a deep learning model.

Cytopathology : official journal of the British Society for Clinical Cytology
BACKGROUND: Intraoperative pathological diagnosis of central nervous system (CNS) tumours is essential to planning patient management in neuro-oncology. Frozen section slides and cytological preparations provide architectural and cellular information...

An efficient deep learning framework for P300 evoked related potential detection in EEG signal.

Computer methods and programs in biomedicine
BACKGROUND: Incorporating the time-frequency localization properties of Gabor transform (GT), the complexity understandings of convolutional neural network (CNN), and histogram of oriented gradients (HOG) efficacy in distinguishing positive peaks can...

An Anomaly Intrusion Detection for High-Density Internet of Things Wireless Communication Network Based Deep Learning Algorithms.

Sensors (Basel, Switzerland)
Telecommunication networks are growing exponentially due to their significant role in civilization and industry. As a result of this very significant role, diverse applications have been appeared, which require secured links for data transmission. Ho...

Deep learning-based ensemble modeling of Vibrio parahaemolyticus concentration in marine environment.

Environmental monitoring and assessment
Vibrio parahaemolyticus (V.p) is a marine pathogenic bacterium that poses a high risk to human health and shellfish industry, yet an effective regional-scale nowcasting model for managing the risk remains lacking. This study presents the first region...

Contrast-Enhanced Ultrasound with Deep Learning with Attention Mechanisms for Predicting Microvascular Invasion in Single Hepatocellular Carcinoma.

Academic radiology
RATIONALE AND OBJECTIVES: Prediction of microvascular invasion (MVI) status of hepatocellular carcinoma (HCC) holds clinical significance for decision-making regarding the treatment strategy and evaluation of patient prognosis. We developed a deep le...