AIMC Topic: Algorithms

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Incremental learning algorithm for large-scale semi-supervised ordinal regression.

Neural networks : the official journal of the International Neural Network Society
As a special case of multi-classification, ordinal regression (also known as ordinal classification) is a popular method to tackle the multi-class problems with samples marked by a set of ranks. Semi-supervised ordinal regression (SSOR) is especially...

Artificial intelligence for the detection, prediction, and management of atrial fibrillation.

Herzschrittmachertherapie & Elektrophysiologie
The present article reviews the state of the art of machine learning algorithms for the detection, prediction, and management of atrial fibrillation (AF), as well as of the development and evaluation of artificial intelligence (AI) in cardiology and ...

[Ethical, legal and social implications in the use of artificial intelligence-based technologies in surgery : Principles, implementation and importance for the user].

Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen
Ethical, legal and social aspects are gaining increasingly more attention in the development and during the initial clinical application of medical devices. The introduction of elements of artificial intelligence (AI) and systems which are using AI m...

Contextual Detection of Pedestrians and Vehicles in Orthophotography by Fusion of Deep Learning Algorithms.

Sensors (Basel, Switzerland)
In the context of smart cities, monitoring pedestrian and vehicle movements is essential to recognize abnormal events and prevent accidents. The proposed method in this work focuses on analyzing video streams captured from a vertically installed came...

Comparing Sampling Strategies for Tackling Imbalanced Data in Human Activity Recognition.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) using wearable sensors is an increasingly active research topic in machine learning, aided in part by the ready availability of detailed motion capture data from smartphones, fitness trackers, and smartwatches. The go...

An Efficient Deep Learning Model to Detect COVID-19 Using Chest X-ray Images.

International journal of environmental research and public health
The tragic pandemic of COVID-19, due to the Severe Acute Respiratory Syndrome coronavirus-2 or SARS-CoV-2, has shaken the entire world, and has significantly disrupted healthcare systems in many countries. Because of the existing challenges and contr...

Examination of blood samples using deep learning and mobile microscopy.

BMC bioinformatics
BACKGROUND: Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventional blood tests are performed in medical laboratories by specialized professionals and are time and...

Analysis of the Model for Sports Enhancing Human Health Using Data Mining.

Journal of healthcare engineering
The problems of low reliability and the high fitting degree of mutual information feature extraction of traditional sports to human health enhancement model are analyzed. We analyze and study the sports to human health enhancement model using data mi...

Asynchronous learning for actor-critic neural networks and synchronous triggering for multiplayer system.

ISA transactions
In this paper, based on actor-critic neural network structure and reinforcement learning scheme, a novel asynchronous learning algorithm with event communication is developed, so as to solve Nash equilibrium of multiplayer nonzero-sum differential ga...

Injection attack estimation of networked control systems subject to hidden DoS attack.

ISA transactions
This paper is concerned with the injection attack estimation for a class of networked control systems with Deny-of-Service (DoS) attack, where unknown signals are injected into the sensor reading and actuator. The main goal is to design an estimator ...