AIMC Topic: Machine Learning

Clear Filters Showing 16151 to 16160 of 34417 articles

Sensor Screening Methodology for Virtually Sensing Transmission Input Loads of a Wind Turbine Using Machine Learning Techniques and Drivetrain Simulations.

Sensors (Basel, Switzerland)
The ongoing trend of building larger wind turbines (WT) to reach greater economies of scale is contributing to the reduction in cost of wind energy, as well as the increase in WT drivetrain input loads into uncharted territories. The resulting intens...

A Systematic Study on Electromyography-Based Hand Gesture Recognition for Assistive Robots Using Deep Learning and Machine Learning Models.

Sensors (Basel, Switzerland)
Upper limb amputation severely affects the quality of life and the activities of daily living of a person. In the last decade, many robotic hand prostheses have been developed which are controlled by using various sensing technologies such as artific...

Mitigating Bias and Error in Machine Learning to Protect Sports Data.

Computational intelligence and neuroscience
One of the essential processes in modern sports is doping control. In recent years, specialized methods of artificial intelligence and large-scale data analysis have been used to make faster and simpler detection of violations of international regula...

A Guide for the Application of Statistics in Biomedical Studies Concerning Machine Learning and Artificial Intelligence.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
With the plethora of machine learning (ML) analyses published in the orthopaedic literature within the last 5 years, several attempts have been made to enhance our understanding of what exactly ML means and how it is used. At its most fundamental lev...

Meaningless Applications and Misguided Methodologies in Artificial Intelligence-Related Orthopaedic Research Propagates Hype Over Hope.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
There exists great hope and hype in the literature surrounding applications of artificial intelligence (AI) to orthopaedic surgery. Between 2018 and 2021, a total of 178 AI-related articles were published in orthopaedics. However, for every 2 origina...

Physics-constrained deep active learning for spatiotemporal modeling of cardiac electrodynamics.

Computers in biology and medicine
The development of computational modeling and simulation have immensely benefited the study of cardiac disease mechanisms and facilitated the optimal disease diagnosis and treatment design. The dynamic propagation of cardiac electrical signals are of...

What Actually Works for Activity Recognition in Scenarios with Significant Domain Shift: Lessons Learned from the 2019 and 2020 Sussex-Huawei Challenges.

Sensors (Basel, Switzerland)
From 2018 to 2021, the Sussex-Huawei Locomotion-Transportation Recognition Challenge presented different scenarios in which participants were tasked with recognizing eight different modes of locomotion and transportation using sensor data from smartp...

Artificial intelligence in cancer target identification and drug discovery.

Signal transduction and targeted therapy
Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying...

DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks.

PloS one
Development of automated analysis tools for "single ion channel" recording is hampered by the lack of available training data. For machine learning based tools, very large training sets are necessary with sample-by-sample point labelled data (e.g., 1...

A machine learning approach applied to gynecological ultrasound to predict progression-free survival in ovarian cancer patients.

Archives of gynecology and obstetrics
In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promising tool for implementing complex multi-parametric decision-making algorithms. Regarding ovarian cancer (OC), despite the standardization of features t...