Latest AI and machine learning research in geriatrics for healthcare professionals.
The collection of updated data on social contact patterns following the COVID-19 pandemic disruptions is crucial for future epidemiological assessments and evaluating non-pharmaceutical interventions (NPIs) based on physical distancing. We conducted two waves of an online survey in March 2022 and March 2023 in Italy, gathering data from a representative population sample on direct (verbal/physic...
Deformable image registration is a fundamental requirement for medical image analysis. Recently, transformers have been widely used in deep learning-based registration methods for their ability to capture long-range dependency via self-attention (SA). However, the high computation and memory loads of SA (growing quadratically with the spatial resolution) hinder transformers from processing subtl...
Vertebral compression fractures (VCFs) are a common and potentially serious consequence of osteoporosis. Yet, they often remain undiagnosed. Opportu...
Deep neural network (DNN)-based joint source and channel coding is proposed for privacy-aware end-to-end image transmission against multiple eavesdr...
Visual Language Models have demonstrated remarkable capabilities across tasks, including visual question answering and image captioning. However, mo...
Recent advancements in generative AI have flourished the development of highly adept Large Language Models (LLMs) that integrate diverse data types ...
Flowcharts are typically presented as images, driving the trend of using vision-language models (VLMs) for end-to-end flowchart understanding. Howev...
We propose a new simulator, training approach, and policy architecture, collectively called SOUS VIDE, for end-to-end visual drone navigation. Our t...
Alzheimer's Disease (AD) is a significant and growing public health concern. Investigating alterations in speech and language patterns offers a prom...
Synthesizing natural human motion that adapts to complex environments while allowing creative control remains a fundamental challenge in motion synt...
In recent years, large-scale models have achieved significant advancements, accompanied by the emergence of numerous high-quality benchmarks for eva...
BACKGROUND/AIMS: Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that severely affects cognitive functions and memory. Early dete...
Current ophthalmology clinical workflows are plagued by over-referrals, long waits, and complex and heterogeneous medical records. Large language mo...
Stress is a pervasive global health issue that can lead to severe mental health problems. Early detection offers timely intervention and prevention ...
Boosted by Multi-modal Large Language Models (MLLMs), text-guided universal segmentation models for the image and video domains have made rapid prog...
This study introduces an AI-driven platform for continuous and passive patient monitoring in hospital settings, developed by LookDeep Health. Levera...
Neural Radiance Field (NeRF)-based volumetric video has revolutionized visual media by delivering photorealistic Free-Viewpoint Video (FVV) experien...
This paper presents a comprehensive exploration of the phenomenon of data redundancy in video understanding, with the aim to improve computational e...
White matter hyperintensities (WMH) of presumed vascular origin are a magnetic resonance imaging (MRI)-based biomarker of cerebral small vessel diseas...
This study explores fine-tuning multilingual ASR (Automatic Speech Recognition) models, specifically OpenAI's Whisper-Tiny, to improve performance i...