Latest AI and machine learning research in medicare for healthcare professionals.
Online platforms like Pinterest hosting vast content collections traditionally rely on manual curation or user-generated search logs to create keyword landing pages (KLPs) -- topic-centered collection pages that serve as entry points for content discovery. While manual curation ensures quality, it doesn't scale to millions of collections, and search log approaches result in limited topic coverag...
Precise Event Spotting (PES) aims to identify events and their class from long, untrimmed videos, particularly in sports. The main objective of PES is to detect the event at the exact moment it occurs. Existing methods mainly rely on features from a large pre-trained network, which may not be ideal for the task. Furthermore, these methods overlook the issue of imbalanced event class distribution...
Uncertainty quantification is necessary for developers, physicians, and regulatory agencies to build trust in machine learning predictors and improv...
Multimodal large language models (MLLMs) have enabled open-world visual understanding by injecting visual input as extra tokens into large language ...
Quantum federated learning (QFL) merges the privacy advantages of federated systems with the computational potential of quantum neural networks (QNN...
We introduce COU: Common Objects Underwater, an instance-segmented image dataset of commonly found man-made objects in multiple aquatic and marine e...
The signature kernel is a recent state-of-the-art tool for analyzing high-dimensional sequential data, valued for its theoretical guarantees and str...
Long-context Multimodal Large Language Models (MLLMs) that incorporate long text-image and text-video modalities, demand substantial resources as th...
A sentiment analysis system powered by machine learning was created in this study to improve real-time social network public opinion monitoring. For...
Regulatory texts are inherently long and complex, presenting significant challenges for information retrieval systems in supporting regulatory offic...
Novel research aimed at text-to-image (T2I) generative AI safety often relies on publicly available datasets for training and evaluation, making the...
Medicare fraud poses a substantial challenge to healthcare systems, resulting in significant financial losses and undermining the quality of care pr...
Testing processes usually aim at high coverage, but loops severely limit coverage ambitions since the number of iterations is generally not predicta...
Existing Large Vision-Language Models (LVLMs) can process inputs with context lengths up to 128k visual and text tokens, yet they struggle to genera...
Purpose: Comprehensive legal medicine documentation includes both an internal but also an external examination of the corpse. Typically, this docume...
Accurately locating key moments within long videos is crucial for solving long video understanding (LVU) tasks. However, existing benchmarks are eit...
Single-cell proteomics (SCP) is transforming our understanding of biological complexity by shifting from bulk proteomics, where signals are averaged...
The efficient processing of long context poses a serious challenge for large language models (LLMs). Recently, retrieval-augmented generation (RAG) ...
Mental health remains a critical global challenge, with increasing demand for accessible, effective interventions. Large language models (LLMs) offe...
Access to health resources is a critical determinant of public well-being and societal resilience, particularly during public health crises when dem...