Geriatrics

Feature Integration of FDG PET Brain Imaging Using Deep Learning for Sensitive Cognitive Decline Detection

Background Distinguishing individuals with cognitive decline (CD), including early Alzheimers disease, from cognitively normal (CN) individuals is essential for improving diagnostic accuracy and enabling timely intervention. Positron emission tomography (PET) captures functional brain alterations associated with CD, but its broader application is often limited by cost and radiation exposure. To en...

Li-ViP3D++: Query-Gated Deformable Camera-LiDAR Fusion for End-to-End Perception and Trajectory Prediction

End-to-end perception and trajectory prediction from raw sensor data is one of the key capabilities for autonomous driving. Modular pipelines restrict information flow and can amplify upstream errors. Recent query-based, fully differentiable perception-and-prediction (PnP) models mitigate these issues, yet the complementarity of cameras and LiDAR in the query-space has not been sufficiently explor...

NuiWorld: Exploring a Scalable Framework for End-to-End Controllable World Generation

World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main...

VC-Bench: Pioneering the Video Connecting Benchmark with a Dataset and Evaluation Metrics

While current video generation focuses on text or image conditions, practical applications like video editing and vlogging often need to seamlessly co...

Cortex-Grounded Diffusion Models for Brain Image Generation

Synthetic neuroimaging data can mitigate critical limitations of real-world datasets, including the scarcity of rare phenotypes, domain shifts across ...

Early Dementia Diagnosis in Older Adults through Machine Learning: A Cross-Sectional fMRI Data Analysis

Background: Early diagnosis of dementia can significantly improve care planning and patient outcomes while delaying progression. Machine learning algo...

SqueakPose Studio: An end-to-end platform for pose estimation and real-time edge-AI deployment

Accurate pose estimation underpins quantitative analysis of behavior, yet many deep learning-based tracking tools remain optimized for offline workflo...

End-to-end deep learning versus machine learning for biomarker discovery in cancer genomes

Background: Accurate determination of genomic biomarkers from tumor sequencing is fundamental to precision oncology, informing disease classification ...

Learning temporal embeddings from electronic health records of chronic kidney disease patients

We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations wit...

A retrieval-augmented generation large language model framework for accurate dementia identification from electronic health records

Objective Accurate and scalable disease phenotyping from electronic health records (EHRs) is foundational for predictive modeling and precision medici...

NanoSimFormer: An end-to-end Transformer-based simulator for nanopore sequencing signal data

Nanopore sequencing has achieved a new standard of accuracy with the advent of R10.4.1 flow cell and high-performance Transformer-based basecalling mo...

Association of Deep Learning-Derived Temporalis Sarcopenia with Mortality in Acute Ischemic Stroke

Background: Sarcopenia is associated with mortality and morbidity following acute ischemic stroke (AIS), but the diagnosis requires specialized equipm...

A Cautionary Tale of Self-Supervised Learning for Imaging Biomarkers: Alzheimer's Disease Case Study

Discovery of sensitive and biologically grounded biomarkers is essential for early detection and monitoring of Alzheimer's disease (AD). Structural MR...

Masked Modeling for Human Motion Recovery Under Occlusions

Human motion reconstruction from monocular videos is a fundamental challenge in computer vision, with broad applications in AR/VR, robotics, and digit...

DSGym: A Holistic Framework for Evaluating and Training Data Science Agents

Data science agents promise to accelerate discovery and insight-generation by turning data into executable analyses and findings. Yet existing data sc...

Rethinking Drug-Drug Interaction Modeling as Generalizable Relation Learning

Drug-drug interaction (DDI) prediction is central to drug discovery and clinical development, particularly in the context of increasingly prevalent po...

Masked Modeling for Human Motion Recovery Under Occlusions

Human motion reconstruction from monocular videos is a fundamental challenge in computer vision, with broad applications in AR/VR, robotics, and digit...

Radiomic Analysis of Breast Thermal Images Using Thermalytix: A Multi-case, Multit-reader Study Against Manual Interpretation

Objective: To evaluate the performance of Thermalytix, an artificial intelligence-enhanced breast thermal imaging analysis software, against unaided m...

Integrating Acoustic, Prosodic, and Phonological Features for Automatic Alzheimer's Detection

Early and accurate diagnosis of Alzheimer's Disease (AD) is critical for effective intervention. While previous studies have explored speech-based bio...

Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling

Accurately modeling longitudinal brain MRI progression is crucial for understanding neurodegenerative diseases and predicting individualized structura...