AIMC Topic: Algorithms

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Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation.

Scientific reports
Traffic congestion forecasting is one of the major elements of the Intelligent Transportation Systems (ITS). Traffic congestion in urban road networks significantly influences sustainability by increasing air pollution levels. Efficient congestion ma...

Machine learning based predictive model of the risk of Tourette syndrome with SHAP value interpretation: a retrospective observational study.

Scientific reports
Tourette syndrome is a relatively prevalent neurological condition, particularly among children, characterized by sudden, involuntary, repetitive movements or vocalizations. Contemporary diagnostic approaches for Tourette syndrome (TS) primarily rely...

Utilizing Dual-Channel Graph and Hypergraph Convolution Network to Discover Microbes Underlying Disease Traits.

Journal of chemical information and modeling
Discovering microbes underlying disease traits opens up opportunities for the diagnosis and effective treatment of diseases. However, traditional methods are often based on biological experiments, which are not only time-consuming but also costly, dr...

Combining graph neural network and Mamba to capture local and global tissue spatial relationships in whole slide images.

Scientific reports
In computational pathology, extracting and representing spatial features from gigapixel whole slide images (WSIs) are fundamental tasks, but due to their large size, WSIs are typically segmented into smaller tiles. A critical aspect of analyzing WSIs...

An advanced three stage lightweight model for underwater human detection.

Scientific reports
This study presents StarEye, a lightweight deep learning model designed for underwater human body detection (UHBD) that addresses the challenges of complex underwater environments. The proposed model incorporates several innovative components: a comp...

Bio inspired optimization techniques for disease detection in deep learning systems.

Scientific reports
Numerous contemporary computer-aided disease detection methodologies predominantly depend on feature engineering techniques; yet, they possess several drawbacks, including the presence of redundant features and excessive time consumption. Conventiona...

Dual retrieving and ranking medical large language model with retrieval augmented generation.

Scientific reports
Recent advancements in large language models (LLMs) have significantly enhanced text generation across various sectors; however, their medical application faces critical challenges regarding both accuracy and real-time responsiveness. To address thes...

Single-shot reconstruction of three-dimensional morphology of biological cells in digital holographic microscopy using a physics-driven neural network.

Nature communications
Recent advances in deep learning-based image reconstruction techniques have led to significant progress in phase retrieval using digital in-line holographic microscopy (DIHM). However, existing phase retrieval methods have technical limitations in 3D...

Machine learning for predicting retention times of chiral analytes chromatographically separated by CMPA technique.

Journal of chromatography. A
Chiral mobile phase additive (CMPA) technique is an attractive method for chromatographic enantioseparation of chiral analytes. However, establishing chromatographic separation and analysis methods for given chiral analytes often requires extensive t...