Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 4,501 to 4,510 of 203,842 articles

Empirical analysis of adversarial robustness in 3D Gaussian Splatting under multi-view inconsistency attacks.

Scientific reports Jun 1, 2026
3D Gaussian Splatting has emerged as a promising technique for real-time novel view synthesis, achieving rendering quality comparable to neural radiance fields while enabling significantly faster inference. Despite its growing adoption in various app... read more 

Spatial distribution and environmental attributes dataset of China's large-scale data centers in 2024.

Scientific data Jun 1, 2026
With the rapid development of artificial intelligence, the energy consumption of large-scale data centers continues to grow. Understanding the spatial distribution of large-scale data centers is important for optimizing power system planning, increas... read more 

A hybrid CNN-DNN model for battery remaining useful life RUL prediction.

Scientific reports Jun 1, 2026
Accurate prediction of the Remaining Useful Life of lithium-ion batteries is essential for enhancing reliability, safety, and maintenance planning in energy storage systems. This study proposes an optimized hybrid deep learning framework that integra... read more 

Spatial differentiation and driving mechanisms of traditional villages based on geo-explainable artificial intelligence.

Scientific reports Jun 1, 2026
Traditional villages represent important cultural landscapes in China; however, their spatial patterns and driving mechanisms remain unclear in the context of rapid urbanization. This study selected 194 traditional villages and 4,705 spatial grids wi... read more 

Prediction of the surface roughness of Ti-6Al-4 V alloy during surface grinding using machine learning models.

Scientific reports Jun 1, 2026
This study presents a machine learning (ML)-based approach to predict surface roughness, Ra during dry grinding of Ti-6Al-4 V alloy using Decision Tree, Random Forest, Gradient Boosting, Extreme Gradient Boosting (XGBoost), Linear Regression, and Pol... read more 

Submanifold sparse convolutional networks for automated 3D segmentation of kidneys and kidney tumours in computed tomography.

Scientific reports Jun 1, 2026
Accurate delineation of kidney tumours in Computed Tomography (CT) is essential for downstream quantitative analysis and precision oncology that could enable personalised treatments, but manual segmentation is a specialised task, time-consuming and d... read more 

Hybrid deep learning and ES-MDA for pressure transient inversion in radial composite reservoirs.

Scientific reports Jun 1, 2026
Accurate characterization of reservoir heterogeneity is important for improving reservoir management and production forecasting. This study presents a hybrid workflow for permeability estimation in structured radial composite reservoirs using deep le... read more 

Overcoming resolution constraints in automated colony counting via a high-performance deep learning framework using SAHI.

Scientific reports Jun 1, 2026
Lightweight models perform poorly in bacterial colony counting when high-resolution Petri dish images are downscaled to 640 × 640 pixels. This study addresses this issue using a tiled training and SAHI-based tiled inference pipeline. Full-resolution ... read more 

Computational modeling of Monte Carlo-enhanced PINNs for fractional order differential models with memory effects.

Scientific reports Jun 1, 2026
Fractional differential equations (FDEs) have been used extensively to model systems with memory and non-local dynamics, but the high computational cost of evaluation of a fractional derivative means that their numerical solution is difficult to calc... read more 

Bayesian convolutional front-end based uncertainty-aware hybrid quantum-classical image classification.

Scientific reports Jun 1, 2026
Quantum machine learning on noisy intermediate-scale quantum (NISQ) devices often suffers from noise sensitivity, small-data overfitting, and miscalibrated predictive confidence. We propose an uncertainty-aware hybrid Bayesian quantum neural network ... read more 
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