AIMC Topic: Neural Networks, Computer

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ATST-Net: A method to identify early symptoms in the upper and lower extremities of PD.

Medical engineering & physics
Bradykinesia, a core symptom of motor disorders in Parkinson's disease (PD), is a major criterion for screening early PD patients in clinical practice. Currently, many studies have proposed automatic assessment schemes for bradykinesia in PD. However...

Deep Aramaic: Towards a synthetic data paradigm enabling machine learning in epigraphy.

PloS one
Epigraphy is witnessing a growing integration of artificial intelligence, notably through its subfield of machine learning (ML), especially in tasks like extracting insights from ancient inscriptions. However, scarce labeled data for training ML algo...

Synthetic Low-Energy Monochromatic Image Generation in Single-Energy Computed Tomography System Using a Transformer-Based Deep Learning Model.

Journal of imaging informatics in medicine
While dual-energy computed tomography (DECT) technology introduces energy-specific information in clinical practice, single-energy CT (SECT) is predominantly used, limiting the number of people who can benefit from DECT. This study proposed a novel m...

The Classification of Lumbar Spondylolisthesis X-Ray Images Using Convolutional Neural Networks.

Journal of imaging informatics in medicine
We aimed to develop and validate a deep convolutional neural network (DCNN) model capable of accurately identifying spondylolysis or spondylolisthesis on lateral or dynamic X-ray images. A total of 2449 lumbar lateral and dynamic X-ray images were co...

Collagen and elastic fibers assessment of the human heart valves for age estimation in Thais using image analysis.

Forensic science, medicine, and pathology
The study investigated the relationship between the histological compositions of the tricuspid, pulmonary, mitral, and aortic valves, and age. All 85 fresh human hearts were obtained with an age range between 20 and 90 years. The central area of the ...

Span-based few-shot event detection via aligning external knowledge.

Neural networks : the official journal of the International Neural Network Society
Few-shot Event Detection (FSED) aims to identify novel event types in new domains with very limited annotated data. Previous PN-based (Prototypical Network) joint methods suffer from insufficient learning of token-wise label dependency and inaccurate...

Tissue specific tumor-gene link prediction through sampling based GNN using a heterogeneous network.

Medical & biological engineering & computing
A tissue sample is a valuable resource for understanding a patient's symptoms and health status in relation to tumor growth. Recent research seeks to establish a connection between tissue-specific tumor samples and genetic markers (genes). This break...

A multi-featured expression recognition model incorporating attention mechanism and object detection structure for psychological problem diagnosis.

Physiology & behavior
Expression is the main method for judging the emotional state and psychological condition of the human body, and the prediction of changes in facial expressions can effectively determine the mental health of a person, thus avoiding serious psychologi...

Development and application of a deep learning-based comprehensive early diagnostic model for chronic obstructive pulmonary disease.

Respiratory research
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a frequently diagnosed yet treatable condition, provided it is identified early and managed effectively. This study aims to develop an advanced COPD diagnostic model by integrating deep lear...

Prediction of jumbo drill penetration rate in underground mines using various machine learning approaches and traditional models.

Scientific reports
Estimating penetration rates of Jumbo drills is crucial for optimizing underground mining drilling processes, aiming to reduce costs and time. This study investigates various regression and machine learning methods, including Multilayer Perceptron (M...