AIMC Topic: Humans

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EOG Signal Classification with Wavelet and Supervised Learning Algorithms KNN, SVM and DT.

Sensors (Basel, Switzerland)
The work carried out in this paper consists of the classification of the physiological signal generated by eye movement called Electrooculography (EOG). The human eye performs simultaneous movements, when focusing on an object, generating a potential...

Saliency Map and Deep Learning in Binary Classification of Brain Tumours.

Sensors (Basel, Switzerland)
The paper was devoted to the application of saliency analysis methods in the performance analysis of deep neural networks used for the binary classification of brain tumours. We have presented the basic issues related to deep learning techniques. A s...

Harvesting the Power of Artificial Intelligence for Surgery: Uses, Implications, and Ethical Considerations.

The American surgeon
Artificial intelligence is rapidly advancing, especially with the advent of ChatGPT technology, and its role in the world of medicine is expanding. Within surgery, AI has the capacity to improve efficiency and results in surgical treatments; however,...

An artificial neural network approach for rational decision-making in borderline orthodontic cases: A preliminary analytical observational in silico study.

Journal of orthodontics
INTRODUCTION: Artificial intelligence (AI) technology has transformed the way healthcare functions in the present scenario. In orthodontics, expert systems and machine learning have aided clinicians in making complex, multifactorial decisions. One su...

Development and validation of a deep learning radiomics nomogram for preoperatively differentiating thymic epithelial tumor histologic subtypes.

European radiology
OBJECTIVES: Using contrast-enhanced computed tomography (CECT) and deep learning technology to develop a deep learning radiomics nomogram (DLRN) to preoperative predict risk status of patients with thymic epithelial tumors (TETs).

In silico prediction of hERG blockers using machine learning and deep learning approaches.

Journal of applied toxicology : JAT
The human ether-à-go-go-related gene (hERG) is associated with drug cardiotoxicity. If the hERG channel is blocked, it will lead to prolonged QT interval and cause sudden death in severe cases. Therefore, it is important to evaluate the hERG-blocking...

An adaptive reinforcement learning-based multimodal data fusion framework for human-robot confrontation gaming.

Neural networks : the official journal of the International Neural Network Society
Playing games between humans and robots have become a widespread human-robot confrontation (HRC) application. Although many approaches were proposed to enhance the tracking accuracy by combining different information, the problems of the intelligence...

Comprehensive dose evaluation of a Deep Learning based synthetic Computed Tomography algorithm for pelvic Magnetic Resonance-only radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Magnetic Resonance (MR)-only radiotherapy enables the use of MR without the uncertainty of MR-Computed Tomography (CT) registration. This requires a synthetic CT (sCT) for dose calculations, which can be facilitated by a novel...

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review.

Computers in biology and medicine
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality globally. At early stages, CVDs appear with minor symptoms and progressively get worse. The majority of people experience symptoms such as exhaustion, ...

Explainable semi-supervised deep learning shows that dementia is associated with small, avocado-shaped clocks with irregularly placed hands.

Scientific reports
The clock drawing test is a simple and inexpensive method to screen for cognitive frailties, including dementia. In this study, we used the relevance factor variational autoencoder (RF-VAE), a deep generative neural network, to represent digitized cl...