AI Medical Compendium Topic

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Computer Systems

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Eye-gesture control of computer systems via artificial intelligence.

F1000Research
BACKGROUND: Artificial Intelligence (AI) offers transformative potential for human-computer interaction, particularly through eye-gesture recognition, enabling intuitive control for users and accessibility for individuals with physical impairments.

RVCNet: A hybrid deep neural network framework for the diagnosis of lung diseases.

PloS one
Early evaluation and diagnosis can significantly reduce the life-threatening nature of lung diseases. Computer-aided diagnostic systems (CADs) can help radiologists make more precise diagnoses and reduce misinterpretations in lung disease diagnosis. ...

Editorial Topical Collection: "Explainable and Augmented Machine Learning for Biosignals and Biomedical Images".

Sensors (Basel, Switzerland)
Machine learning (ML) is a well-known subfield of artificial intelligence (AI) that aims at developing algorithms and statistical models able to empower computer systems to automatically adapt to a specific task through experience or learning from da...

Real-Time Calibration-Free Musculotendon Kinematics for Neuromusculoskeletal Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neuromusculoskeletal (NMS) models enable non-invasive estimation of clinically important internal biomechanics. A critical part of NMS modelling is the estimation of musculotendon kinematics, which comprise musculotendon unit lengths, moment arms, an...

YOLO-IHD: Improved Real-Time Human Detection System for Indoor Drones.

Sensors (Basel, Switzerland)
In the field of unmanned systems, the combination of artificial intelligence with self-operating functionalities is becoming increasingly important. This study introduces a new method for autonomously detecting humans in indoor environments using unm...

Effect of Light-Emitting Grid Panel on Indoor Aquaculture for Measuring Fish Growth.

Sensors (Basel, Switzerland)
This study is related to Smart Aqua Farm, which combines artificial intelligence (AI) and Internet of things (IoT) technology. This study aimed to monitor fish growth in indoor aquaculture while automatically measuring the average size and area in re...

Non-invasive load monitoring based on deep learning to identify unknown loads.

PloS one
With the rapid development of smart grids, society has become increasingly urgent to solve the problems of low energy utilization efficiency and high energy consumption. In this context, load identification has become a key element in formulating sci...

Application of eHealth Tools in Anticoagulation Management After Cardiac Valve Replacement: Scoping Review Coupled With Bibliometric Analysis.

JMIR mHealth and uHealth
BACKGROUND: Anticoagulation management can effectively prevent complications in patients undergoing cardiac valve replacement (CVR). The emergence of eHealth tools provides new prospects for the management of long-term anticoagulants. However, there ...

Modeling failures in smart grids by a bilinear logistic regression approach.

Neural networks : the official journal of the International Neural Network Society
Modeling and recognizing events in complex systems through machine learning techniques is a challenging task. Especially if the model is constrained to be explainable and interpretable, while ensuring high levels of accuracy. In this paper, we adopt ...

A Deep-Learning Empowered, Real-Time Processing Platform of fNIRS/DOT for Brain Computer Interfaces and Neurofeedback.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brain-Computer Interfaces (BCI) and Neurofeedback (NFB) approaches, which both rely on real-time monitoring of brain activity, are increasingly being applied in rehabilitation, assistive technology, neurological diseases and behavioral disorders. Fun...