AI Medical Compendium

A cascaded group attention mechanism-based object detection algorithm for construction and demolition waste.

Scientific reports Mar 2, 2026

Accurate object detection is crucial for managing construction and demolition waste (CDW). However, existing deep-learning models often exhibit limited performance in detecting small objects within complex environments. This study proposes a YOLOv11-... read more

New energy vehicle fault identification based on improved activation functions and parameter-free attention mechanisms.

Scientific reports Mar 2, 2026

The drive system of New Energy Vehicles (NEVs) is a core component ensuring the safe and efficient operation of vehicles. Key components such as batteries, motors, and inverters are prone to faults under complex operating conditions, severely affecti... read more

M[Formula: see text]DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson's disease(PD) progression using whole-blood RNA sequencing data.

Scientific reports Mar 2, 2026

With emerging single-cell transcriptomics data, deep learning approaches have enabled the diagnosis of neurodegenerative disorders such as Parkinson's disease(PD). Based on whole-blood RNA sequencing data, the graph neural network has predicted Parki... read more

A hybrid optimal feature selection and Conv-LSTM model (OFSCL) for short-term energy demand forecasting in distribution substations of Ahvaz, Iran.

Scientific reports Mar 2, 2026

An integrated physics-guided machine learning approach for predicting asphalt concrete fracture parameters.

Scientific reports Mar 2, 2026

Comprehensive machine learning identifies anoikis signatures predicting therapeutic resistance and survival in gastric cancer.

Scientific reports Mar 2, 2026

CSWin-MDKDNet: cross-shaped window network with multi-dimensional fusion and knowledge distillation for medical image segmentation.

Scientific reports Mar 2, 2026

In recent years, deep learning has achieved significant advancements in medical image segmentation. Medical image segmentation is fundamental to computer-aided diagnosis, yet challenges persist in balancing local detail preservation and global contex... read more

Prioritizing neglected food species in nutritional studies using expert-knowledge and explainable AI.

Scientific reports Mar 2, 2026

Food biodiversity is vital for human health and the development of sustainable food systems. However, research on neglected and underutilized species is limited by funding, uneven research capacity, and the challenge of balancing ecological, cultural... read more

Reliable ECG classification using parallel hybrid models with limited resources.

Scientific reports Mar 2, 2026

Retraction Note: Comparing ANI-2x, ANI-1ccx neural networks, force field, and DFT methods for predicting conformational potential energy of organic molecules.

Scientific reports Mar 2, 2026

Artificial Intelligence Medical Compendium

A cascaded group attention mechanism-based object detection algorithm for construction and demolition waste.

New energy vehicle fault identification based on improved activation functions and parameter-free attention mechanisms.

M[Formula: see text]DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson's disease(PD) progression using whole-blood RNA sequencing data.

A hybrid optimal feature selection and Conv-LSTM model (OFSCL) for short-term energy demand forecasting in distribution substations of Ahvaz, Iran.

An integrated physics-guided machine learning approach for predicting asphalt concrete fracture parameters.

Comprehensive machine learning identifies anoikis signatures predicting therapeutic resistance and survival in gastric cancer.

CSWin-MDKDNet: cross-shaped window network with multi-dimensional fusion and knowledge distillation for medical image segmentation.

Prioritizing neglected food species in nutritional studies using expert-knowledge and explainable AI.

Reliable ECG classification using parallel hybrid models with limited resources.

Retraction Note: Comparing ANI-2x, ANI-1ccx neural networks, force field, and DFT methods for predicting conformational potential energy of organic molecules.

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