AIMC Topic: Sports

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A new approach to bioceramics based on tissue reaction of tricalcium phosphate for biomedical and sport applications using machine learning modeling.

Tissue & cell
Tricalcium phosphate (TCP) bioceramics have emerged as a promising option to meet the specific requirements associated with athlete bone fractures. Advanced computational modeling techniques, such as artificial neural networks (ANNs), have been lever...

The optimization and impact of public sports service quality based on the supervised learning model and artificial intelligence.

Scientific reports
Aiming at the optimization of public sports service quality, this study analyzes the public sports service data deeply by constructing a supervised learning model. Firstly, the theoretical framework of this study is established. Secondly, the technic...

Harnessing generative AI in exercise and sports science education: enhancing real-world learning and overcoming traditional barriers in data analysis.

Advances in physiology education
Generative AI (GenAI) offers transformative potential for exercise and sports science education, addressing traditional data analysis and visualization barriers while promoting real-world learning. This Perspectives article explores how integrating G...

Advancing Sports Cardiology: Integrating Artificial Intelligence with Wearable Devices for Cardiovascular Health Management.

ACS applied materials & interfaces
Sports cardiology focuses on athletes' cardiovascular health, yet sudden cardiac death remains a significant concern despite preventative measures. Prolonged physical activity leads to notable cardiovascular adaptations, known as the athlete's heart,...

A Hybrid Approach for Sports Activity Recognition Using Key Body Descriptors and Hybrid Deep Learning Classifier.

Sensors (Basel, Switzerland)
This paper presents an approach for event recognition in sequential images using human body part features and their surrounding context. Key body points were approximated to track and monitor their presence in complex scenarios. Various feature descr...

Object detection in motion management scenarios based on deep learning.

PloS one
In athletes' competitions and daily training, in order to further strengthen the athletes' sports level, it is usually necessary to analyze the athletes' sports actions at a specific moment, in which it is especially important to quickly and accurate...

A parallel CNN architecture for sport activity recognition based on minimal movement data.

Scientific reports
Novel Human Activity Recognition (HAR) methodologies, which are built upon learning algorithms and employ ubiquitous sensors, have achieved remarkable precision in the identification of sports activities. Such progress benefits all age groups of huma...

Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management.

Sensors (Basel, Switzerland)
Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performance, and health management. This work examines how AI is advancing the role of sports scientists, pa...

Assessing the effectiveness of fuzzy logic-based models for predicting sports event outcomes: A CRITIC-VIKOR approach.

PloS one
Incorporating fuzzy logic-based models into sports prediction has generated significant interest due to the intricate nature of athletic events and the many factors influencing their outcomes. This study evaluates the effectiveness of fuzzy logic-bas...

The analysis of generative adversarial network in sports education based on deep learning.

Scientific reports
The importance of mental health is increasingly emphasized in modern society. The assessment of mental health qualities among college and university students as the future workforce holds significant significance. Therefore, this study, aiming to str...