AIMC Topic: Humans

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Automatic mandible segmentation from CT image using 3D fully convolutional neural network based on DenseASPP and attention gates.

International journal of computer assisted radiology and surgery
PURPOSE: In cranio-maxillofacial surgery, it is of great clinical significance to segment mandible accurately and automatically from CT images. However, the connected region and blurred boundary in teeth and condyles make the process challenging. At ...

A Long Short-Term Memory Network Stock Price Prediction with Leading Indicators.

Big data
The accuracy of the prediction of stock price fluctuations is crucial for investors, and it helps investors manage funds better when formulating trading strategies. Using forecasting tools to get a predicted value that is closer to the actual value f...

Practical fine-grained learning based anomaly classification for ECG image.

Artificial intelligence in medicine
As a widely used vital sign within cardiology, Electrocardiography (ECG) provides the basis for assessing heart function and diagnosing cardiovascular diseases. Automated anomaly detection for ECG plays an important role in improving patient diagnosi...

Artificial intelligence-driven assessment of radiological images for COVID-19.

Computers in biology and medicine
Artificial Intelligence (AI) methods have significant potential for diagnosis and prognosis of COVID-19 infections. Rapid identification of COVID-19 and its severity in individual patients is expected to enable better control of the disease individua...

Development of convolutional neural networks for recognition of tenogenic differentiation based on cellular morphology.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The use of automated systems for image recognition is highly preferred for regenerative medicine applications to evaluate stem cell differentiation early in the culturing state with non-invasive methodologies instead of inva...

xECGNet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias.

Computer methods and programs in biomedicine
Background and objectiveDetecting abnormal patterns within an electrocardiogram (ECG) is crucial for diagnosing cardiovascular diseases. We start from two unresolved problems in applying deep-learning-based ECG classification models to clinical pract...

Cross-Gram matrices and their use in transfer learning: Application to automatic REM detection using heart rate.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: while traditional sleep staging is achieved through the visual - expert-based - annotation of a polysomnography, it has the disadvantages of being unpractical and expensive. Alternatives have been developed over the years t...

Hierarchical CNN-based occlusal surface morphology analysis for classifying posterior tooth type using augmented images from 3D dental surface models.

Computer methods and programs in biomedicine
OBJECTIVE: 3D Digitization of dental model is growing in popularity for dental application. Classification of tooth type from single 3D point cloud model without assist of relative position among teeth is still a challenging task.

Heart disease prediction using supervised machine learning algorithms: Performance analysis and comparison.

Computers in biology and medicine
Machine learning and data mining-based approaches to prediction and detection of heart disease would be of great clinical utility, but are highly challenging to develop. In most countries there is a lack of cardiovascular expertise and a significant ...