Latest AI and machine learning research in us health policy for healthcare professionals.
Chronic disease management relies on regular patient-provider interactions to follow-up on disease progression and control. For Type 2 Diabetes (T2D), current guidelines prescribe fixed time intervals between subsequent primary care visits for all patients, overlooking heterogeneity in clinical trajectories and patient characteristics. This study introduces a Contextual Markov Decision Process (CM...
Valuable critique of generative image models within visual culture and the humanities has emphasized the role of datasets in shaping the images they produce. Yet, close studies of the ideological positions embedded into the mechanism of the models have been neglected, leaving them imagined as "black boxes." In a bid to expand, rather than replace, dataset critique, this paper examines the mechanis...
Anxiety and depression are globally prevalent conditions associated with maladaptive decision making. However, whether affective symptoms primarily am...
Since the U.S. 2013/14 influenza season, the CDC's FluSight Challenge has provided a platform for evaluating influenza forecasting models and fosterin...
Document parsing systems are increasingly deployed in high-stakes, regulated workflows such as mortgage underwriting, financial reporting, supply-chai...
Although large language models (LLMs) have shown promise for discharge summary generation, their value may be greater in longer hospitalizations, wher...
Abstract Background: Artificial Intelligence (AI) is increasingly integrated into healthcare systems worldwide and medical schools worldwide have begu...
Adaptive behavior requires flexibly shifting between exploiting familiar rewards and exploring novel opportunities. These explore-exploit decisions ar...
Cesarean Scar Defect (CSD) is one of the most prevalent complications following cesarean delivery. Transvaginal ultrasonography is widely used for pri...
Background Increasingly accessible satellite imagery provides scalable measures of the built and natural environment relevant to population health. Ho...
The immense value of public gene expression repositories is constrained by the lack of compatibility among datasets generated from diverse experimenta...
Hybrid mechanistic models, physical priors with learned residuals, promise to reduce the data required for good decisions, but have no computable crit...
Purpose: To demonstrate the feasibility of prostate MRI at low-field and provide an optimised low-field prostate MRI protocol. Methods: We acquired bi...
Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. However, their...
Objective: To propose and retrospectively validate an integrated framework addressing three barriers to clinical translation of readmission prediction...
Background: Chronic conditions such as hypertension can significantly disrupt daily life and emotional wellbeing. The interaction between patients' pe...
Clinical value set authoring -- the task of identifying all codes in a standardized vocabulary that define a clinical concept -- is a recurring bottle...
Classifier-free Guidance (CFG) lets practitioners trade-off fidelity against diversity in Diffusion Models (DMs). The practicality of CFG is however h...
Extending LLM context windows is hindered by scarce high-quality long-context data. Recent methods synthesize data with genuine long-range dependencie...
The present study evaluates the real-world clinical predictive performance of FDA-authorized artificial intelligence (AI) devices used in radiology, f...