Medicaid

The Swiss Integrated Care (INCA) Study: Description of a Novel Prospective Cohort of Patients and Caregivers in Reimbursed Informal Care

Methods INCA is a prospective, single-center cohort study with nationwide recruitment. Participation is open to adult patients and informal caregivers who provide paid informal care through home care agencies (Spitex organizations) in Switzerland. Eligible participants are enrolled consecutively. The cohorts primary outcome is health-related quality of life of patients, assessed monthly through pa...

Processing strategies for improving cortical thickness correspondence between low-field and high-field MRI in young people

Portable low-field MRI systems are a promising complement to conventional high-field systems, enabling broader access to MRI. However, correspondence in cortical thickness estimates between low- and high-field MRI in young people remains limited despite its importance for neurodevelopment and psychopathology. To evaluate how multiple low-field image processing approaches improve cortical thickness...

Geometry-aware Depth-guided Representation Learning for Structure-preserving Low-light Image Enhancement

Low-light degradation reduces image visibility and weakens structural cues that are important for visual representation and scene understanding. Exist...

Nickel and Dimed: How a Common Earth Element is Short-Changing Our Health

Nickel has been studied for a long time as an environmental contaminant but less so in its connection to population health. It does not announce itsel...

Real-World Validation of Machine Learning Models for HIV Treatment Adherence Prediction and Care Gap Quantification: A Multi-Country Analysis of 192,732 Clinical Records

Delayed diagnosis and poor antiretroviral therapy (ART) adherence remain primary drivers of HIV-related morbidity in low-resource settings, yet real-w...

NexOP: Joint Optimization of NEX-Aware k-space Sampling and Image Reconstruction for Low-Field MRI

Modern low-field magnetic resonance imaging (MRI) technology offers a compelling alternative to standard high-field MRI, with portable, low-cost syste...

Reading in the Dark: Low-light Scene Text Recognition

Accurate text recognition in low-light environments is essential for intelligent systems in applications ranging from autonomous vehicles to smart sur...

Generalizing intensive care AI across time scales in resource-limited settings

Temporal resolution of physiological monitoring in intensive care varies widely across healthcare systems. Artificial intelligence models assume a uni...

UDAPose: Unsupervised Domain Adaptation for Low-Light Human Pose Estimation

Low-visibility scenarios, such as low-light conditions, pose significant challenges to human pose estimation due to the scarcity of annotated low-ligh...

Harnessing exhaled breath for lung cancer early detection, results from the ExPeL study

Background Scalable, non invasive tools are critically needed to improve early lung cancer detection and optimize primary care referral pathways. We e...

DarkDriving: A Real-World Day and Night Aligned Dataset for Autonomous Driving in the Dark Environment

The low-light conditions are challenging to the vision-centric perception systems for autonomous driving in the dark environment. In this paper, we pr...

UAVBench and UAVIT-1M: Benchmarking and Enhancing MLLMs for Low-Altitude UAV Vision-Language Understanding

Multimodal Large Language Models (MLLMs) have made significant strides in natural images and satellite remote sensing images. However, understanding l...

Care Plan Generation for Underserved Patients Using Multi-Agent Language Models: Applying Nash Game Theory to Optimize Multiple Objectives

Background Clinicians in care management programs are often in low supply relative to patient demand, especially in US Medicaid programs, and must sim...

Real-World Data for Predicting Rapid Relapse Triple Negative Cancer: A Study Using NCDB and EHR Data

Background: Many patients with triple-negative breast cancer (TNBC), particularly those who are older, Black, or insured by Medicaid, do not receive g...

When Less Is Enough: Low-Rank Structure in DNA Sequence-to-Function Models

Motivation: The rapid success of deep learning sequence-to-function (S2F) models has driven a trend toward ever larger architectures for regulatory ge...

High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model

Computation in recurrent networks of neurons has been hypothesized to occur at the level of low-dimensional latent dynamics, both in artificial system...

From Enhancement to Understanding: Build a Generalized Bridge for Low-light Vision via Semantically Consistent Unsupervised Fine-tuning

Low-level enhancement and high-level visual understanding in low-light vision have traditionally been treated separately. Low-light enhancement impr...

Robust Low-light Scene Restoration via Illumination Transition

Synthesizing normal-light novel views from low-light multiview images is an important yet challenging task, given the low visibility and high ISO no...

Pushing the Limit of Post-Training Quantization.

Recently, post-training quantization (PTQ) has become the de facto way to produce efficient low-precision neural networks without long-time retraining...

ReF-LLE: Personalized Low-Light Enhancement via Reference-Guided Deep Reinforcement Learning

Low-light image enhancement presents two primary challenges: 1) Significant variations in low-light images across different conditions, and 2) Enhan...