AIMC Topic: Algorithms

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BiomedRAG: A retrieval augmented large language model for biomedicine.

Journal of biomedical informatics
Retrieval-augmented generation (RAG) involves a solution by retrieving knowledge from an established database to enhance the performance of large language models (LLM). , these models retrieve information at the sentence or paragraph level, potential...

A multi-level feature fusion artificial neural network for classification of acoustic emission signals.

Annals of the New York Academy of Sciences
In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract ...

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...

Squat Motion of a Humanoid Robot Using Three-Particle Model Predictive Control and Whole-Body Control.

Sensors (Basel, Switzerland)
Squatting is a fundamental and crucial movement, often employed as a basic test during robot commissioning, and it plays a significant role in some service industries and in cases when robots perform high-dynamic movements like jumping. Therefore, ac...

Real-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition.

Sensors (Basel, Switzerland)
Sensor-based gesture recognition on mobile devices is critical to human-computer interaction, enabling intuitive user input for various applications. However, current approaches often rely on server-based retraining whenever new gestures are introduc...

Development of immune-derived molecular markers for preeclampsia based on multiple machine learning algorithms.

Scientific reports
Preeclampsia (PE) is a major pregnancy-specific cardiovascular complication posing latent life-threatening risks to mothers and neonates. The contribution of immune dysregulation to PE is not fully understood, highlighting the need to explore molecul...

AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks.

eLife
Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chemical and genetic networks. The emerging field of diverse intelligence investigates the problem-solvi...

DTI-MHAPR: optimized drug-target interaction prediction via PCA-enhanced features and heterogeneous graph attention networks.

BMC bioinformatics
Drug-target interactions (DTIs) are pivotal in drug discovery and development, and their accurate identification can significantly expedite the process. Numerous DTI prediction methods have emerged, yet many fail to fully harness the feature informat...

GRL-PUL: predicting microbe-drug association based on graph representation learning and positive unlabeled learning.

Molecular omics
Extensive research has confirmed the widespread presence of microorganisms in the human body and their crucial impact on human health, with drugs being an effective method of regulation. Hence it is essential to identify potential microbe-drug associ...

Internal validation of a convolutional neural network pipeline for assessing meibomian gland structure from meibography.

Optometry and vision science : official publication of the American Academy of Optometry
SIGNIFICANCE: Optimal meibography utilization and interpretation are hindered due to poor lid presentation, blurry images, or image artifacts and the challenges of applying clinical grading scales. These results, using the largest image dataset analy...