AIMC Topic: Algorithms

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Generalization of Deep Learning Gesture Classification in Robotic-Assisted Surgical Data: From Dry Lab to Clinical-Like Data.

IEEE journal of biomedical and health informatics
OBJECTIVE: Robotic-assisted minimally invasive surgery (RAMIS) became a common practice in modern medicine and is widely studied. Surgical procedures require prolonged and complex movements; therefore, classifying surgical gestures could be helpful t...

A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels.

IEEE journal of biomedical and health informatics
In this paper, we introduce a new variation of the Convolutional Neural Network Inception block, called Sinc, for sleep stage classification in premature newborn babies using electroencephalogram (EEG). In practice, there are many medical centres whe...

Brain Tumor Classification Using Fine-Tuned GoogLeNet Features and Machine Learning Algorithms: IoMT Enabled CAD System.

IEEE journal of biomedical and health informatics
In the healthcare research community, Internet of Medical Things (IoMT) is transforming the healthcare system into the world of the future internet. In IoMT enabled Computer aided diagnosis (CAD) system, the Health-related information is stored via t...

Few-Shot Learning for Deformable Medical Image Registration With Perception-Correspondence Decoupling and Reverse Teaching.

IEEE journal of biomedical and health informatics
Deformable medical image registration estimates corresponding deformation to align the regions of interest (ROIs) of two images to a same spatial coordinate system. However, recent unsupervised registration models only have correspondence ability wit...

Clinical Text Data Categorization and Feature Extraction Using Medical-Fissure Algorithm and Neg-Seq Algorithm.

Computational intelligence and neuroscience
A large amount of patient information has been gathered in Electronic Health Records (EHRs) concerning their conditions. An EHR, as an unstructured text document, serves to maintain health by identifying, treating, and curing illnesses. In this resea...

A Prediction Model of Health Development Based on Linear Sequential Extreme Learning Machine Algorithm Matrix.

Computational intelligence and neuroscience
The rapid development of social economy not only increases people's living pressure but also reduces people's health. Looking for a healthy development prediction model has become a domestic concern. Based on the analysis of the influencing factors o...

A Study of Feature Construction Based on Least Squares and RBF Neural Networks in Sports Training Behaviour Prediction.

Computational intelligence and neuroscience
This paper examines the problem of athletes' training in sports, exploring the methods and means by which athletes can perform difficult movements in which they normally make minor training errors in order to achieve better competition results and pl...

Effects of Integrated Fuzzy Logic PID Controller on Satellite Antenna Tracking System.

Computational intelligence and neuroscience
An electrical device that transforms the electricity into the waves of radio and vice versa is termed the antenna. Its main deployment is in the transmitter and receiver of the antenna. While transmission, the transmitter of radio at the extremities ...

Design and Implementation of a UAV-Based Airborne Computing Platform for Computer Vision and Machine Learning Applications.

Sensors (Basel, Switzerland)
Visual sensing of the environment is crucial for flying an unmanned aerial vehicle (UAV) and is a centerpiece of many related applications. The ability to run computer vision and machine learning algorithms onboard an unmanned aerial system (UAS) is ...

iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Immunogenetics
Cancer is a terrible disease, recent studies reported that tumor T cell antigens (TTCAs) may play a promising role in cancer treatment. Since experimental methods are still expensive and time-consuming, it is highly desirable to develop automatic com...