AIMC Topic: Algorithms

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Towards Single Camera Human 3D-Kinematics.

Sensors (Basel, Switzerland)
Markerless estimation of 3D Kinematics has the great potential to clinically diagnose and monitor movement disorders without referrals to expensive motion capture labs; however, current approaches are limited by performing multiple de-coupled steps t...

RANSAC for Robotic Applications: A Survey.

Sensors (Basel, Switzerland)
Random Sample Consensus, most commonly abbreviated as RANSAC, is a robust estimation method for the parameters of a model contaminated by a sizable percentage of outliers. In its simplest form, the process starts with a sampling of the minimum data n...

Application of Machine Learning in Intelligent Medical Image Diagnosis and Construction of Intelligent Service Process.

Computational intelligence and neuroscience
The introduction of digital technology in the healthcare industry is marked by ongoing difficulties with implementation and use. Slow progress has been made in unifying different healthcare systems, and much of the globe still lacks a fully integrate...

Principles and Validations of an Artificial Intelligence-Based Recommender System Suggesting Acceptable Food Changes.

The Journal of nutrition
BACKGROUND: Along with the popularity of smartphones, artificial intelligence-based personalized suggestions can be seen as promising ways to change eating habits toward more desirable diets.

Multiple machine learning methods aided virtual screening of Na 1.5 inhibitors.

Journal of cellular and molecular medicine
Na 1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion chan...

Diagnosis of Operating Conditions of the Electrical Submersible Pump via Machine Learning.

Sensors (Basel, Switzerland)
In wells that operate by electrical submersible pump (ESP), the use of automation tools becomes essential in the interpretation of data. However, the fact that the wells work with automated systems does not guarantee the early diagnosis of operating ...

A New Approach to Optimize SVM for Insulator State Identification Based on Improved PSO Algorithm.

Sensors (Basel, Switzerland)
The failure of insulators may seriously threaten the safe operation of the power system, where the state detection of high-voltage insulators is a must for the normal and safe operation of the power system. Based on the data of insulators in aerial i...

Automated estimation of ischemic core volume on noncontrast-enhanced CT via machine learning.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BACKGROUND: Accurate estimation of ischemic core on baseline imaging has treatment implications in patients with acute ischemic stroke (AIS). Machine learning (ML) algorithms have shown promising results in estimating ischemic core using routine nonc...

Noninvasive Tracking of Every Individual in Unmarked Mouse Groups Using Multi-Camera Fusion and Deep Learning.

Neuroscience bulletin
Accurate and efficient methods for identifying and tracking each animal in a group are needed to study complex behaviors and social interactions. Traditional tracking methods (e.g., marking each animal with dye or surgically implanting microchips) ca...

An accurate prediction of the origin for bone metastatic cancer using deep learning on digital pathological images.

EBioMedicine
BACKGROUND: Determining the origin of bone metastatic cancer (OBMC) is of great significance to clinical therapeutics. It is challenging for pathologists to determine the OBMC with limited clinical information and bone biopsy.