Medicare

Human-level learning of complex novel tasks as theory-based modelling, exploration and planning.

Humans are remarkable in their ability to quickly learn to perform complex tasks. Reinforcement learning (RL) has long been proposed as a model of human learning, and while leading machine RL models have surpassed human expertise at many classic board games and video games, they require vast experience to learn successfully-none of today's algorithms accounts for humans' ability to learn so many d...

A meta-analysis of gut microbiome research in malnourished African populations: a natural language processing approach.

Malnutrition still affects millions of children in Africa. Changes in the gut microbiome have been implicated in malnutrition, but there has been inconsistent nomenclature of microbes. This meta-analysis reviews the microbiome literature using natural language processing (NLP) methods. We searched PubMed for gut microbiome studies of undernourished children living in low- and middle-income countri...

Natural Language Processing of Clinical Notes for Cancer Research and Patient Care Prior to Widespread Adoption of Generative AI: Scoping Review.

BACKGROUND: Clinical notes are the most abundant data type within electronic health records; however, their highly unstructured format presents signif...

A Natural Language Processing Framework for Structuring and Visualizing Clinical Trial Eligibility Criteria at Scale: Protocol for a Quantitative Study.

BACKGROUND: Eligibility criteria are essential to clinical trial design, guiding recruitment, and ensuring patient safety and scientific rigor. Howeve...

Evaluating Encoder and Decoder Models for Extended Clinical Concept Recognition in Japanese Clinical Texts: Comparative Study With Weighted Soft Matching.

BACKGROUND: Extracting medical knowledge for secondary purposes, such as diagnostic support, continues to pose a substantial challenge. Conventional n...

TOPOS: target organ prediction on scout views for automated CT scan planning.

BACKGROUND: Overscanning is a common issue in CT planning, leading to unnecessary radiation exposure. PURPOSE: To develop a deep learning model to seg...

MPAN: A Multi-Prototype Adaptive Network for Few-Shot EEG-Based Biometric Recognition.

Biometric recognition based on electroencephalography (EEG), which captures intrinsic neural dynamics via scalp-recorded electrical activity, has show...

Evaluating AI-Mediated Health Communication via Large Language Model-Based Frequently Asked Questions Rewriting to Foster Clinical Trial Participation: Comparative Survey Study.

BACKGROUND: Effective communication about clinical trials is essential, as low enrollment undermines scientific validity and contributes to health car...

Artificial Intelligence Electrocardiogram and Left Ventricular Systolic Dysfunction in Kenya.

IMPORTANCE: Early detection of risk of heart failure with reduced ejection fraction remains challenging in resource-limited settings due to limited ac...

Predicting the risk of venous thromboembolism events in older adults with rheumatoid arthritis after initiating targeted disease-modifying antirheumatic drugs: a comparison of the random survival forest and regularized cox regression models.

OBJECTIVES: To develop a random survival forest (RSF) machine learning (ML) model for predicting venous thromboembolism (VTE) risk in rheumatoid arthr...

AIEdit: Alignment-free genome assembly polisher trained on spaced seed match patterns.

Polishing, the process of correcting base-level errors in genome assemblies, is a critical step for ensuring accuracy in downstream analyses, such as ...

Surgical and hormonal gender-affirming care: cross-domain determinants and artificial intelligence-enabled expansion.

Gender-affirming surgery (GAS) and gender-affirming hormone therapy (GAHT) and are evidence-based components of care that support the health and well-...

Risk and Protective Factors Associated With HIV-Related Mortality in Children Receiving Antiretroviral Therapy: A Model-Based Meta-Regression.

IMPORTANCE: Mortality among children and young adolescents receiving antiretroviral therapy (ART) remains substantially higher in resource-limited set...

Machine Learning Prediction and Reducing Overdoses With Electronic Health Record Nudges (mPROVEN) in the Primary Care Setting: Protocol for a Cluster Randomized Controlled Trial.

BACKGROUND: Opioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated...

Automated Logical Observation Identifiers Names and Codes mapping with biomedical natural language processing models: enabling scalable health information exchange via the Open Concept Lab.

OBJECTIVES: Efficient exchange of health information requires consistent representation of clinical concepts across laboratories, hospitals, and publi...

Mapping the Research Landscape of Ageing Population: A Bibliometric Study.

BACKGROUND AND OBJECTIVES: The ageing population is a critical global issue shaped by demographic transitions. Despite growing research, a comprehensi...

Realization of Long Axial Field-of-View PET Technology in the Clinic and Research Environment.

Long axial field-of-view (AFOV) PET-CT instruments have significantly higher sensitivity than conventional PET scanners allowing for reduced scan time...

Wood you believe it-Detecting copper with hyperspectral imaging.

Enhancing circularity and promoting the cascade use of wood resources, currently considered non-recyclable despite containing considerable amounts of ...

CO coadsorption effects on the water-gas shift reaction over Cu clusters on Cu(111): insights from the machine learning force field and microkinetic modeling.

CO-induced Cu clustering has been observed experimentally and theoretically, yet its catalytic implications remain insufficiently understood. Here, we...

eDNA and AI Identification Reveal Complementary Signals in Phytoplankton Monitoring.

Phytoplankton regulates aquatic energy transfer and biogeochemical cycling, yet accurately characterizing community composition remains challenging be...