Latest AI and machine learning research in medicare for healthcare professionals.
Develop and deploy a real-time, EHR-integrated machine learning phenotype to identify emergency department (ED) patients with opioid use disorder (OUD) for prospective clinical trial screening and buprenorphine initiation. We conducted a multi-phase study across three EDs in a single United States health system from 2014 to 2025. Using visit-level data available at or before triage, we trained a r...
An effective Multi-Agent Path Finding (MAPF) algorithm must efficiently plan paths for multiple agents while adhering to constraints, ensuring safe navigation from start to goal. However, due to partial observability, agents often struggle to determine optimal strategies. Thus, developing a robust information fusion method is crucial for addressing these challenges. Information fusion expands the ...
PURPOSE: We aim to evaluate various proxy selection methods within the context of high-dimensional propensity score (hdPS) analysis. This study aimed ...
In post-disaster scenarios, effective rescue operations hinge on deploying robots equipped with sophisticated path planning algorithms capable of navi...
In many applications, such as coverage exploration and search and rescue missions, accurately assessing environmental complexity is valuable for perfo...
The editorial, "Clinical and translational mode of single-cell measurements: An artificial intelligent single-cell," introduces the innovative clinica...
Large language models (LLMs) are empowering decision-making in several applications, including tool or API usage and answering multiple-choice quest...
Our aim is to learn to solve long-horizon decision-making problems in highly-variable, combinatorially-complex robotics domains given raw sensor inp...
Over time, the distribution of medical image data drifts due to factors such as shifts in patient demographics, acquisition devices, and disease man...
Long COVID continues to challenge public health by affecting a significant segment of individuals who have recovered from acute SARS-CoV-2 infection...
An image may convey a thousand words, but a video composed of hundreds or thousands of image frames tells a more intricate story. Despite significan...
Recent advances in flexible keyword spotting (KWS) with text enrollment allow users to personalize keywords without uttering them during enrollment....
Row-level lineage explains what input rows produce an output row through a data processing pipeline, having many applications like data debugging, a...
Seagrass meadows play a crucial role in marine ecosystems, providing benefits such as carbon sequestration, water quality improvement, and habitat p...
Vision-Language Models (VLMs) have shown promising capabilities in handling various multimodal tasks, yet they struggle in long-context scenarios, p...
We introduce Neptune, a benchmark for long video understanding that requires reasoning over long time horizons and across different modalities. Many...
We aim to develop a model-based planning framework for world models that can be scaled with increasing model and data budgets for general-purpose ma...
Coverage path planning (CPP) is the task of computing an optimal path within a region to completely scan or survey an area of interest using one or ...
Long-read sequencing technologies can capture entire RNA transcripts in a single sequencing read, reducing the ambiguity in constructing and quantifyi...
Accurate prediction of medical conditions with straight past clinical evidence is a long-sought topic in the medical management and health insurance...