Geriatrics

Latest AI and machine learning research in geriatrics for healthcare professionals.

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SemEval-2025 Task 4: Unlearning sensitive content from Large Language Models

We introduce SemEval-2025 Task 4: unlearning sensitive content from Large Language Models (LLMs). The task features 3 subtasks for LLM unlearning spanning different use cases: (1) unlearn long form synthetic creative documents spanning different genres; (2) unlearn short form synthetic biographies containing personally identifiable information (PII), including fake names, phone number, SSN, emai...

End-to-End Driving with Online Trajectory Evaluation via BEV World Model

End-to-end autonomous driving has achieved remarkable progress by integrating perception, prediction, and planning into a fully differentiable framework. Yet, to fully realize its potential, an effective online trajectory evaluation is indispensable to ensure safety. By forecasting the future outcomes of a given trajectory, trajectory evaluation becomes much more effective. This goal can be achi...

xML-workFlow: an end-to-end explainable scikit-learn workflow for rapid biomedical experimentation

Motivation: Building and iterating machine learning models is often a resource-intensive process. In biomedical research, scientific codebases can l...

Flexible and Explainable Graph Analysis for EEG-based Alzheimer's Disease Classification

Alzheimer's Disease is a progressive neurological disorder that is one of the most common forms of dementia. It leads to a decline in memory, reason...

Accelerating Causal Network Discovery of Alzheimer Disease Biomarkers via Scientific Literature-based Retrieval Augmented Generation

The causal relationships between biomarkers are essential for disease diagnosis and medical treatment planning. One notable application is Alzheimer...

SViQA: A Unified Speech-Vision Multimodal Model for Textless Visual Question Answering

Multimodal models integrating speech and vision hold significant potential for advancing human-computer interaction, particularly in Speech-Based Vi...

GKAN: Explainable Diagnosis of Alzheimer's Disease Using Graph Neural Network with Kolmogorov-Arnold Networks

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that poses significant diagnostic challenges due to its complex etiology. Graph...

Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents

Computer use agents automate digital tasks by directly interacting with graphical user interfaces (GUIs) on computers and mobile devices, offering s...

Evaluating Traditional, Deep Learning and Subfield Methods for Automatically Segmenting the Hippocampus From MRI.

Given the relationship between hippocampal atrophy and cognitive impairment in various pathological conditions, hippocampus segmentation from MRI is a...

Apr 1 2025 40143669
NAD_MCNN: Combining Protein Language Models and Multiwindow Convolutional Neural Networks for Deacetylase NAD+ Binding Site Prediction.

Sirtuins, a class of NAD+ -dependent deacetylases, play a key role in aging, metabolism, and longevity. Their interaction with NAD+ at the catalytic s...

Apr 1 2025 40183480
Dynamic and Static Structure-Function Coupling With Machine Learning for the Early Detection of Alzheimer's Disease.

The progression of Alzheimer's disease (AD) involves complex changes in brain structure and function that are driven by their interaction, making stru...

Apr 1 2025 40193134
Artificial intelligence in colorectal surgery multidisciplinary team approach-From innovation to application.

Artificial intelligence (AI) has played a novel role in aiding healthcare system functions and enhancing the patient experience. Multidisciplinary tea...

Apr 1 2025 40285450
Over-the-Air Edge Inference via End-to-End Metasurfaces-Integrated Artificial Neural Networks

In the Edge Inference (EI) paradigm, where a Deep Neural Network (DNN) is split across the transceivers to wirelessly communicate goal-defined featu...

RIG: Synergizing Reasoning and Imagination in End-to-End Generalist Policy

Reasoning before action and imagining potential outcomes (i.e., world models) are essential for embodied agents operating in complex open-world envi...

AI2Agent: An End-to-End Framework for Deploying AI Projects as Autonomous Agents

As AI technology advances, it is driving innovation across industries, increasing the demand for scalable AI project deployment. However, deployment...

An End-to-End Comprehensive Gear Fault Diagnosis Method Based on Multi-Scale Feature-Level Fusion Strategy

To satisfy the requirements of the end-to-end fault diagnosis of gears, an integrated intelligent method of fault diagnosis for gears using accelera...

Spatiotemporal Learning of Brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention for Cognitive and Psychiatric Applications

Understanding how the brain's complex nonlinear dynamics give rise to adaptive cognition and behavior is a central challenge in neuroscience. These ...

The Mind in the Machine: A Survey of Incorporating Psychological Theories in LLMs

Psychological insights have long shaped pivotal NLP breakthroughs, including the cognitive underpinnings of attention mechanisms, formative reinforc...

MedCL: Learning Consistent Anatomy Distribution for Scribble-supervised Medical Image Segmentation

Curating large-scale fully annotated datasets is expensive, laborious, and cumbersome, especially for medical images. Several methods have been prop...

DynaGraph: Interpretable Multi-Label Prediction from EHRs via Dynamic Graph Learning and Contrastive Augmentation

Learning from longitudinal electronic health records is limited if it does not capture the temporal trajectories of the patient's state in a clinica...

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