AIMC Topic: Machine Learning

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Assessment of Physical Fitness and Health Status of Athletes Based on Intelligent Medical Treatment under Machine Learning.

Computational intelligence and neuroscience
Machine learning is an interdisciplinary study of how to make computer programs perform similar to human learning, and its techniques are widely used in the medical industry. The purpose of this paper is to study how to use machine learning-based int...

Optimization of Ideological and Political Education Strategies in Colleges and Universities Based on Deep Learning.

Computational intelligence and neuroscience
In the current technological world, artificially intelligent deep learning techniques are adapted in many fields. This advanced technology is also used in the field of education. In this study, people will conduct research on the optimization of ideo...

Artificial intelligence-based clinical decision support in pediatrics.

Pediatric research
Machine learning models may be integrated into clinical decision support (CDS) systems to identify children at risk of specific diagnoses or clinical deterioration to provide evidence-based recommendations. This use of artificial intelligence models ...

Using machine learning to impact on long-term clinical care: principles, challenges, and practicalities.

Pediatric research
The rise of machine learning in healthcare has significant implications for paediatrics. Long-term conditions with significant disease heterogeneity comprise large portions of the routine work performed by paediatricians. Improving outcomes through d...

Fitness Movement Types and Completeness Detection Using a Transfer-Learning-Based Deep Neural Network.

Sensors (Basel, Switzerland)
Fitness is important in people's lives. Good fitness habits can improve cardiopulmonary capacity, increase concentration, prevent obesity, and effectively reduce the risk of death. Home fitness does not require large equipment but uses dumbbells, yog...

Towards an Explainable Universal Feature Set for IoT Intrusion Detection.

Sensors (Basel, Switzerland)
As IoT devices' adoption grows rapidly, security plays an important role in our daily lives. As part of the effort to counter these security threats in recent years, many IoT intrusion detection datasets were presented, such as TON_IoT, BoT-IoT, and ...

Interpretable machine learning approach to analyze the effects of landscape and meteorological factors on mosquito occurrences in Seoul, South Korea.

Environmental science and pollution research international
Mosquitoes are the underlying cause of various public health and economic problems. In this study, patterns of mosquito occurrence were analyzed based on landscape and meteorological factors in the metropolitan city of Seoul. We evaluated the influen...

Systematic comparison of machine learning algorithms to develop and validate predictive models for periodontitis.

Journal of clinical periodontology
AIM: The aim of this study was to compare the validity of different machine learning algorithms to develop and validate predictive models for periodontitis.

Informing geometric deep learning with electronic interactions to accelerate quantum chemistry.

Proceedings of the National Academy of Sciences of the United States of America
Predicting electronic energies, densities, and related chemical properties can facilitate the discovery of novel catalysts, medicines, and battery materials. However, existing machine learning techniques are challenged by the scarcity of training dat...

IoT and Satellite Sensor Data Integration for Assessment of Environmental Variables: A Case Study on NO.

Sensors (Basel, Switzerland)
This paper introduces a novel approach to increase the spatiotemporal resolution of an arbitrary environmental variable. This is achieved by utilizing machine learning algorithms to construct a satellite-like image at any given time moment, based on ...