Medicare

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 cross-species predictive performance being consistently worse than within-species performance. In this study, a novel Nucleotide-Level Deep Neural Network (NLDNN) is first proposed to predict TF binding within or across species. NLDNN regards the task...

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 bones and methods to improve model performance.59 enchondromas and 53 ACTs in long bones confirmed by pathology were collected retrospectively. The features were extracted from preoperative CT images of these patients, and least absolute shrinkage and s...

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...

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...

Socio-demographic predictors of not having private dental insurance coverage: machine-learning algorithms may help identify the disadvantaged.

BACKGROUND: For accessing dental care in Canada, approximately 62% of the population has employment-based insurance, 6% have some publicly funded cove...

Enhancing the coverage of SemRep using a relation classification approach.

OBJECTIVE: Relation extraction is an essential task in the field of biomedical literature mining and offers significant benefits for various downstrea...

Prediction of incomplete immunization among under-five children in East Africa from recent demographic and health surveys: a machine learning approach.

The World Health Organization as part of the goal of universal vaccination coverage by 2030 for all individuals. The global under-five mortality rate ...

ChatGPT: Literate or intelligent about UN sustainable development goals?

Generative AI tools, such as ChatGPT, are progressively transforming numerous sectors, demonstrating a capacity to impact human life dramatically. Thi...

Multi-modal long document classification based on Hierarchical Prompt and Multi-modal Transformer.

In the realm of long document classification (LDC), previous research has predominantly focused on modeling unimodal texts, overlooking the potential ...

Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.

This study aimed to: (1) validate a natural language processing (NLP) system developed for the home health care setting to identify signs and symptoms...

Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes.

OBJECTIVE: This study aims to explore the opinions on the insurance coverage of artificial intelligence (AI), as categorized based on the distinct val...

Detection and coverage estimation of purple nutsedge in turf with image classification neural networks.

BACKGROUND: Accurate detection of weeds and estimation of their coverage is crucial for implementing precision herbicide applications. Deep learning (...

Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clinical trial timelines. To meet the planned trial rec...

Assessment of lymph node area coverage with total marrow irradiation and implementation of total marrow and lymphoid irradiation using automated deep learning-based segmentation.

BACKGROUND: Total marrow irradiation (TMI) and total marrow and lymphoid irradiation (TMLI) have the advantages. However, delineating target lesions a...