Geriatrics

Backbone-Agnostic Perturbation-Induced Uncertainty Learning for End-to-End Real-World Image Dehazing

Real-world paired image dehazing remains challenging because haze degradation is spatially non-uniform, illumination-dependent, and physically ambiguous even when haze-free references are available. Existing end-to-end restoration networks usually formulate dehazing as a deterministic mapping from a hazy observation to a clean target, leaving the uncertainty hidden in degraded features, haze prior...

Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts

Accurate diagnostic classification and disease-severity prediction for Alzheimer's disease are hampered by the incompleteness and heterogeneity of real-world clinical data. Left unaddressed, these barriers prevent reliable disease modelling and hinder effective clinical evaluation. Conventional imputation strategies introduce systematic bias, distort inter-feature relationships, and yield overconf...

TextileNet: Towards Zero-shot Text-style Segmentation of Manuscripts

Automatic writer identification systems have progressed remarkably in recent years, yet their deployment in archival paleography remains limited by th...

Machine Learning Models for Osteoporosis Prediction: A Systematic Review and Meta-Analysis

Purpose The application of machine learning (ML) to osteoporosis prediction has expanded rapidly, yet no comprehensive meta-analysis has synthesized t...

An epigenetic speedometer to measure Pace of Aging: FraminghamPACE

Geroscience clinical trials need biomarker surrogate endpoints for healthspan. Leading candidates are omics-based composites developed from machine le...

Early Prediction of Parkinson's Disease Progression by Integrating Research Cohort and Real-World Data Using Knowledge-Anchored Graph Learning

Parkinson disease (PD) progression is highly heterogeneous. Deeply phenotyped longitudinal research cohorts have enabled characterization of PD progre...

Generative AI Models Reveal Dynamic Views of Aging (DyViA) Phenotypes in Healthy Individuals

Background and objectives: In recent years, the need to develop analytical strategies for healthy aging has assumed great importance. In this study, w...

Cognitive-structured Multimodal Agent for Multimodal Understanding, Generation, and Editing

Recent unified multimodal models show a single architecture can jointly perform vision/language understanding and image generation/editing. However, t...

Effect of initiating an ARB- versus ACEI-based regimen on dementia risk, a target trial emulation of 2.5 million US Veterans

Background: Hypertension is a modifiable risk factor for dementia, yet the comparative effectiveness of angiotensin receptor blockers (ARBs) versus an...

Data-driven trajectories of atrophy explain clinical heterogeneity across Lewy body diseases

Background: Lewy body diseases (LBD) collectively share alpha-synuclein Lewy pathology, yet present wide clinical heterogeneity, with overlapping moto...

ROOTQUANT: AUTOMATED ROOT TRAIT QUANTIFICATION FROMMINIRHIZOTRON IMAGES USING DEEP LEARNING

Quantifying root traits such as root length (RL) and root surface area (RSA) from minirhizotron imagery is a valuable approach for overcoming the phen...

When Color Adds Nothing: A Causal Audit of Channel Triplication in Alzheimer's MRI Classification

Medical imaging pipelines routinely copy single-channel grayscale data into three identical RGB channels before classification, usually without justif...

AT-Attn: Temporal-Aware Cross-Attention for Longitudinal Multimodal Alzheimer's Disease Diagnosis

In longitudinal Alzheimer's disease (AD) diagnosis support, clinical and imaging information is often collected at irregular visits. Integrating these...

Asymmetric Focal Loss Improves Graph Neural Network Prediction of Drug-Drug Interactions

Background: Graph neural networks improve computational prediction of polypharmacy side effects, but standard binary cross-entropy training allocates ...

ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening

Electrocardiography (ECG) is one of the most widely used tests for diagnosing cardiovascular disease. Yet several remote clinics still utilize paper E...

Efficient Long-Horizon Learning for Learned Optimization

Learned optimization aims to improve upon hand-designed optimizers (e.g., Adam and Muon) by meta-learning small neural network optimizers over a distr...

Robust Longitudinal Dementia Prediction under Systemic Missingness via Hierarchical Fusion and Test-Time Adaptation

Longitudinal dementia progression prediction is essential for clinical decision-making. However, models often degrade on external cohorts due to syste...

Automated Multisource Electronic Frailty Index in Acute Ischemic Stroke: Development and Clinical Utility

Background: Frailty is common in acute ischemic stroke (AIS) and predicts poor outcomes, but is not routinely captured in acute stroke care. Manual fr...

TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving

Bird's-Eye View (BEV) end-to-end instance prediction has emerged as a robust paradigm for autonomous driving perception, effectively mitigating the er...

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, informa...