Medicare

Optimal Pair Matching Combined with Machine Learning Predicts a Significant Reduction in Myocardial Infarction Risk in African Americans Following Omega-3 Fatty Acid Supplementation.

Conflicting clinical trial results on omega-3 highly unsaturated fatty acids (n-3 HUFA) have prompted uncertainty about their cardioprotective effects. While the VITAL trial found no overall cardiovascular benefit from n-3 HUFA supplementation, its substantial African American (AfAm) enrollment provided a unique opportunity to explore racial differences in response to n-3 HUFA supplementation. The...

Multi-metric comparison of machine learning imputation methods with application to breast cancer survival.

Handling missing data in clinical prognostic studies is an essential yet challenging task. This study aimed to provide a comprehensive assessment of the effectiveness and reliability of different machine learning (ML) imputation methods across various analytical perspectives. Specifically, it focused on three distinct classes of performance metrics used to evaluate ML imputation methods: post-impu...

Task sharing for increasing access to obstetric ultrasonography: a formative qualitative study of nurse-led scanning with telemedicine review in Kenya.

The informal settlements of Nairobi have higher neonatal and infant mortality rates than the average for Nairobi. Universal access to important diagno...

Recruitment in Appalachian, Rural and Older Adult Populations in an Artificial Intelligence World: Study Using Human-Mediated Follow-Up.

BACKGROUND: Participant recruitment in rural and hard-to-reach (HTR) populations can present unique challenges. These challenges are further exacerbat...

Automatic deep learning segmentation of the hippocampus on high-resolution diffusion magnetic resonance imaging and its application to the healthy lifespan.

Diffusion tensor imaging (DTI) can provide unique contrast and insight into microstructural changes with age or disease of the hippocampus, although i...

AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases.

Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalcoholic steatohepatitis) require histologic scoring ...

Determinantal point process attention over grid cell code supports out of distribution generalization.

Deep neural networks have made tremendous gains in emulating human-like intelligence, and have been used increasingly as ways of understanding how the...

Enhanced 3D dose prediction for hypofractionated SRS (gamma knife radiosurgery) in brain tumor using cascaded-deep-supervised convolutional neural network.

Gamma Knife radiosurgery (GKRS) is a well-established technique in radiation therapy (RT) for treating small-size brain tumors. It administers highly ...

Cross-Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide-Level Deep Neural Network.

Cross-species prediction of TF binding remains a major challenge due to the rapid evolutionary turnover of individual TF binding sites, resulting in c...

Computed tomography-based radiomics machine learning models for differentiating enchondroma and atypical cartilaginous tumor in long bones.

To explore the value of CT-based radiomics machine learning models for differentiating enchondroma from atypical cartilaginous tumor (ACT) in long bon...

Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review.

Retrosynthesis aims to efficiently plan the synthesis of desirable chemicals by strategically breaking down molecules into readily available building ...

An ensemble model for accurate prediction of key water quality parameters in river based on deep learning methods.

Deep learning models provide a more powerful method for accurate and stable prediction of water quality in rivers, which is crucial for the intelligen...

United States newspaper and online media coverage of artificial intelligence and radiology from 1998 to 2023.

OBJECTIVE: To evaluate the frequency and content of media coverage pertaining to artificial intelligence (AI) and radiology in the United States from ...

Identifying symptom etiologies using syntactic patterns and large language models.

Differential diagnosis is a crucial aspect of medical practice, as it guides clinicians to accurate diagnoses and effective treatment plans. Tradition...

Risk factors for prediabetes in community-dwelling adults: A generalized estimating equation logistic regression approach with natural language processing insights.

The global prevalence of prediabetes is expected to reach 8.3% (587 million people) by 2045, with 70% of people with prediabetes developing diabetes d...

Exploring the effects of digital technologies in health financing for universal health coverage: a synthesis of country experiences and lessons.

The use of digital technologies (DTs) for health financing receives increased attention in policy, practice and research. However, not much robust evi...

When an extra rejection class meets out-of-distribution detection in long-tailed image classification.

Detecting Out-of-Distribution (OOD) inputs is essential for reliable deep learning in the open world. However, most existing OOD detection methods hav...

Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters.

Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range p...

High-resolution mapping of essential maternal and child health service coverage in Nigeria: a machine learning approach.

BACKGROUND: National-level coverage estimates of maternal and child health (MCH) services mask district-level and community-level geographical inequit...

Scaling neural machine translation to 200 languages.

The development of neural techniques has opened up new avenues for research in machine translation. Today, neural machine translation (NMT) systems ca...