AIMC Topic: Deep Learning

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A parallel and efficient transformer deep learning network for continuous estimation of hand kinematics from electromyographic signals.

Scientific reports
Surface electromyography (EMG) provides a non-invasive human-machine interaction interface that can promote the coherence of human-machine interaction operations. Decomposing surface electromyographic signals into hand joint angles in real time can b...

Interpretable deep learning for personalized energy expenditure prediction using ECG and acceleration signals in incremental exercise.

Scientific reports
Energy expenditure (EE) assessment is crucial in both sports science and health management. However, current EE prediction models often overlook individual differences and lack dynamic correlation analysis between multi-modal data and EE. Building up...

Lung Ultrasound Imaging Dataset for Accurate Detection and Localization of LUS Vertical Artifact.

Scientific data
Lung ultrasound (LUS) vertical artifacts are critical sonographic markers commonly used in evaluating pulmonary conditions such as pulmonary edema, interstitial lung disease, pneumonia, and COVID-19. Accurate detection and localization of these artif...

Image-based DNA sequencing encoding for detecting low-mosaicism somatic mobile element insertions.

Nature communications
Active mobile elements in the human genome can create novel mobile element insertions (MEIs) in somatic tissues. Detection of somatic MEIs, particularly those with low mosaicism, remains a significant challenge due to sequencing artifacts and alignme...

Predicting sequence-specific amplification efficiency in multi-template PCR with deep learning.

Nature communications
Multi-template polymerase chain reaction (PCR) is a critical technique enabling the parallel amplification of diverse DNA molecules, thereby facilitating applications in fields from quantitative molecular biology to DNA data storage. However, non-hom...

Development of machine learning-based mpox surveillance models in a learning health system.

Sexually transmitted infections
OBJECTIVES: This study aimed to develop robust machine learning (ML)-based and deep learning (DL)-based models capable of detecting mpox cases for surveillance efforts using clinical notes.

Automated detection of large vessel occlusion using deep learning: a pivotal multicenter study and reader performance study.

Journal of neurointerventional surgery
BACKGROUND: To evaluate the stand-alone efficacy and improvements in diagnostic accuracy of early-career physicians of the artificial intelligence (AI) software to detect large vessel occlusion (LVO) in CT angiography (CTA).

BONE-Net: A novel hybrid deep-learning model for effective osteoporosis detection.

PloS one
Osteoporosis is a prevalent bone disease characterized by reduced bone density and an elevated risk of fractures, especially in older adults and postmenopausal women. The clinical consequences of osteoporotic fractures extend beyond pain and disabili...

Feature extraction and intelligent diagnosis of ECG signals based on KANs and xLSTM.

Biosensors & bioelectronics
Cardiovascular disease (CVD) is the top cause of mortality globally, making it crucial to diagnose arrhythmias promptly and accurately for the early prevention and treatment of CVD. While numerous methods exist for detecting arrhythmias using ECG sig...

Deep Learning-Enabled Unbiased Precision Toxicity Assessment of Zebrafish Organ Development.

Environmental science & technology
Precise assessment of toxicological effects remains a key bottleneck in biomedical and environmental health assessments. Traditional toxicology relies on macroscopic end points and manual image analysis, which limit sensitivity to structural damage a...