Latest AI and machine learning research in medicare for healthcare professionals.
BACKGROUND: Global inequities in access to cancer diagnostics and treatment contribute to wide variation in cancer mortality-to-incidence ratios (MIRs), a proxy for survival. We aimed to develop an interpretable machine learning framework to quantify country-specific health system contributors to MIR and inform policy prioritization. MATERIALS AND METHODS: We assembled national MIRs from GLOBOCAN ...
Massively parallel genetic screens have been used to map sequence-to-function relationships for a variety of genetic elements1-5. However, as these approaches interrogate only short sequences, it remains challenging to perform high-throughput assays on constructs containing combinations of multiple sequence elements arranged across multi-kb length scales. Overcoming this barrier could accelerate s...
We have trained and externally validated a knowledge-based planning model for radiation therapy planning in the setting of high-grade glioma. Model pe...
Long-tailed data is ubiquitous in real-world applications, posing significant challenges due to imbalanced class distribution and high levels of label...
BACKGROUND: This study presents the design, development, and field evaluation of Vabot, an artificial intelligence (AI)-powered, fully electric autono...
OBJECTIVES: Generative AI chatbots are revolutionizing health education by making complex information more accessible to the public. However, their us...
Adsorbate-adsorbate interaction serves as a critical bridge between macroscopic mass transfer and microscopic adsorption-reaction kinetics in heteroge...
BACKGROUND AND OBJECTIVE: This study introduces the liver cancer segmentator (LCS), a deep learning model designed for automatic and robust segmentati...
Street-level imagery (SLI) is increasingly used in urban analytics for tasks like estimating greenery, conducting transport audits, and assessing faca...
Reproductive performance affects the profitability of a dairy herd. The ability to understand the reproductive capabilities of individual cows and the...
Long COVID is a chronic, multisystem disease with limited response to conventional treatments. While low-dose methylprednisolone has shown effectivene...
Access to eye care remains a global health priority, particularly for underserved populations in rural, Indigenous, and low-income communities. Despit...
The mutation-aware test prioritisation system in this paper uses Graph Neural Networks (GNNs) to combine static program structure, dynamic execution t...
The Korean Longitudinal Study on Digitally Optimized Mental Healthcare is an innovative multicenter trial-ready cohort study. It aims to develop a dig...
OBJECTIVE: With college freshmen under increasing psychological pressures, early detection of those at risk is critical. We applied machine learning t...
BACKGROUND: Risk adjustment models in Medicare Advantage determine annual payments of over $300 billion in public funds to private companies. Policyma...
Multiple imputation is well-established for handling missing data, yet its use in high-dimensional genetic datasets remains limited. Using pharmacokin...
OBJECTIVE: To evaluate the agreement of automation tools with expert evaluators in identifying cases meeting inclusion and exclusion criteria for retr...
Long COVID, or post-acute sequelae of COVID-19 (PASC), is a major global health problem, with cumulative estimates suggesting that around 400 million ...
This article traces the historical evolution and current complexities of clinical documentation, emphasizing its transformation under regulatory, fina...