Healthcare

Deep learning (DL) image registration methods sometimes underperform classical methods, especially when data distribution shifts; this study reveals when each approach excels.

DDGS-CT: A novel direction-disentangled Gaussian splatting method creates realistic X-ray images from CT scans, boosting accuracy and speed for applications such as image-guided surgery and radiothera…

LLMs iteratively discover and refine interpretable dynamical systems models, achieving high accuracy and uncovering new insights; demonstrated by a novel Warfarin model.

AI-powered drug interaction prediction gets a boost! CSSE-DDI uses neural architecture search to customize subgraph selection and encoding, resulting in superior accuracy and efficiency compared to e…

Chimera: a novel 2D state space model effectively captures complex multivariate time series dependencies, achieving superior forecasting, classification, and anomaly detection.

CALANet: Cheap All-Layer Aggregation boosts real-time HAR accuracy by efficiently aggregating features from all layers, achieving state-of-the-art performance on seven benchmark datasets.

Autoregressive Image Diffusion (AID) generates coherent MRI image sequences from undersampled data, outperforming standard diffusion models by exploiting inter-image dependencies.

AI autonomously designs highly effective hybrid digital twins by combining neural networks and mechanistic models, significantly advancing digital twin technology.

AutoDP automates multi-task learning for joint disease prediction on EHRs, significantly improving performance via automated task grouping and architecture search.

Attention boosted Individualized Regression (AIR) provides a novel individualized modeling framework for matrix data, leveraging sample-specific internal relations without needing extra sample similar…

Pattern-BERP, a novel method, boosts biological entity relationship prediction accuracy by 4-23% using association pattern-aware fusion, enhancing interpretability for real-world applications.

Revolutionizing antibody design, ABDPO uses direct energy-based preference optimization and a pre-trained diffusion model to generate high-quality antibodies with low energy and strong binding affinit…

DDL-CXR dynamically generates up-to-date chest X-ray image representations using latent diffusion models, effectively addressing asynchronous multimodal clinical data for improved prediction.

New nonparametric framework explains ML performance gaps across domains by hierarchically decomposing discrepancies due to covariate and conditional outcome shifts, offering detailed variable-level at…

LLMs dynamically adjust restless multi-armed bandit (RMAB) resource allocation policies in public health via human-language commands.

FlowDPO: Revolutionizing 3D structure prediction with flexible probability paths & Direct Preference Optimization for enhanced accuracy and reduced hallucinations.

NeuroPath: A novel deep learning model reveals how brain structure supports brain function by uncovering multi-hop neural pathways, improving brain network analysis accuracy.