AIMC Topic: Algorithms

Clear Filters Showing 7281 to 7290 of 28713 articles

Exploring the potential of pretrained CNNs and time-frequency methods for accurate epileptic EEG classification: a comparative study.

Biomedical physics & engineering express
Prompt diagnosis of epilepsy relies on accurate classification of automated electroencephalogram (EEG) signals. Several approaches have been developed to characterize epileptic EEG data; however, none of them have exploited time-frequency data to eva...

Who are the best passing players in professional soccer? A machine learning approach for classifying passes with different levels of difficulty and discriminating the best passing players.

PloS one
The present study aimed to assess the use of technical-tactical variables and machine learning (ML) classifiers in the automatic classification of the passing difficulty (DP) level in soccer matches and to illustrate the use of the model with the bes...

Machine learning model based on radiomics features for AO/OTA classification of pelvic fractures on pelvic radiographs.

PloS one
Depending on the degree of fracture, pelvic fracture can be accompanied by vascular damage, and in severe cases, it may progress to hemorrhagic shock. Pelvic radiography can quickly diagnose pelvic fractures, and the Association for Osteosynthesis Fo...

Hybrid deep learning approach for sentiment analysis using text and emojis.

Network (Bristol, England)
Sentiment Analysis (SA) is a technique for categorizing texts based on the sentimental polarity of people's opinions. This paper introduces a sentiment analysis (SA) model with text and emojis. The two preprocessed data's are data with text and emoji...

Miller Fisher's Rules and Digital Health: The Best of Both Worlds.

Cerebrovascular diseases (Basel, Switzerland)
BACKGROUND: Professor Fisher's legacy, defined by meticulous observation, curiosity, and profound knowledge, has established a foundational cornerstone in medical practice. However, the advent of automated algorithms and artificial intelligence (AI) ...

Compressing neural networks via formal methods.

Neural networks : the official journal of the International Neural Network Society
Advancements in Neural Networks have led to larger models, challenging implementation on embedded devices with memory, battery, and computational constraints. Consequently, network compression has flourished, offering solutions to reduce operations a...

Application of artificial intelligence and machine learning techniques to the analysis of dynamic protein sequences.

Proteins
We apply methods of Artificial Intelligence and Machine Learning to protein dynamic bioinformatics. We rewrite the sequences of a large protein data set, containing both folded and intrinsically disordered molecules, using a representation developed ...

Particle uptake in cancer cells can predict malignancy and drug resistance using machine learning.

Science advances
Tumor heterogeneity is a primary factor that contributes to treatment failure. Predictive tools, capable of classifying cancer cells based on their functions, may substantially enhance therapy and extend patient life span. The connection between cell...

Microsaccade-inspired event camera for robotics.

Science robotics
Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and texture. How...

Effective prediction of human skin cancer using stacking based ensemble deep learning algorithm.

Network (Bristol, England)
Automated diagnosis of cancer from skin lesion data has been the focus of numerous research. Despite that it can be challenging to interpret these images because of features like colour illumination changes, variation in the sizes and forms of the le...