AIMC Topic: Algorithms

Clear Filters Showing 2801 to 2810 of 28713 articles

An optimized machine learning framework for predicting and interpreting corporate ESG greenwashing behavior.

PloS one
The accurate prediction and interpretation of corporate Environmental, Social, and Governance (ESG) greenwashing behavior is crucial for enhancing information transparency and improving regulatory effectiveness. This paper addresses the limitations i...

Online Unsupervised Adaptation of Latent Representation for Myoelectric Control During User-Decoder Co-Adaptation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Myoelectric control interfaces, which map electromyographic (EMG) signals into control commands for external devices, have applications in active prosthesis control. However, the statistical characteristics of EMG signals change over time (e.g., beca...

Controlling nutritional status score predicts posthepatectomy liver failure: an online interpretable machine learning prediction model.

European journal of gastroenterology & hepatology
BACKGROUND AND AIMS: Posthepatectomy liver failure (PHLF) remains a severe complication after hepatectomy for hepatocellular carcinoma (HCC) and accurate preoperative evaluation and predictive measures are urgently needed. We investigated the impact ...

A unified approach to medical image segmentation by leveraging mixed supervision and self and transfer learning (MIST).

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical image segmentation is important for quantitative disease diagnosis and treatment but relies on accurate pixel-wise labels, which are costly, time-consuming, and require domain expertise. This work introduces MIST (MIxed supervision, Self, and...

Measuring the severity of knee osteoarthritis with an aberration-free fast line scanning Raman imaging system.

Analytica chimica acta
Osteoarthritis (OA) is a major cause of disability worldwide, with symptoms like joint pain, limited functionality, and decreased quality of life, potentially leading to deformity and irreversible damage. Chemical changes in joint tissues precede ima...

Artificial intelligence-based deep learning algorithms for ground-glass opacity nodule detection: A review.

Narra J
Ground-glass opacities (GGOs) are hazy opacities on chest computed tomography (CT) scans that can indicate various lung diseases, including early COVID-19, pneumonia, and lung cancer. Artificial intelligence (AI) is a promising tool for analyzing med...

A general framework for interpretable neural learning based on local information-theoretic goal functions.

Proceedings of the National Academy of Sciences of the United States of America
Despite the impressive performance of biological and artificial networks, an intuitive understanding of how their local learning dynamics contribute to network-level task solutions remains a challenge to this date. Efforts to bring learning to a more...

Machine Learning-Based Computer Vision for Depth Camera-Based Physiotherapy Movement Assessment: A Systematic Review.

Sensors (Basel, Switzerland)
Machine learning-based computer vision techniques using depth cameras have shown potential in physiotherapy movement assessment. However, a comprehensive understanding of their implementation, effectiveness, and limitations remains needed. Following ...

Insight into the Relationships Between Chemical, Protein and Functional Variables in the PBP/GOBP Family in Moths Based on Machine Learning.

International journal of molecular sciences
During their lives, insects must cope with a plethora of chemicals, of which a few will have an impact at the behavioral level. To detect these chemicals, insects use several protein families located in their main olfactory organs, the antennae. Insi...

Rethinking model prototyping through the MedMNIST+ dataset collection.

Scientific reports
The integration of deep learning based systems in clinical practice is often impeded by challenges rooted in limited and heterogeneous medical datasets. In addition, the field has increasingly prioritized marginal performance gains on a few, narrowly...