Medicaid

Clinician Adoption of an Artificial Intelligence Algorithm to Detect Left Ventricular Systolic Dysfunction in Primary Care.

OBJECTIVE: To compare the clinicians' characteristics of "high adopters" and "low adopters" of an ar...

Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models.

A large body of work has suggested that neural populations exhibit low-dimensional dynamics during b...

Comment on "Prediction of impacts on liver enzymes from the exposure of low-dose medical radiations through artificial intelligence algorithms".

Prior knowledge facilitates low homologous protein secondary structure prediction with DSM distillation.

MOTIVATION: Protein secondary structure prediction (PSSP) is one of the fundamental and challenging ...

Deep Learning Empowers Lung Cancer Screening Based on Mobile Low-Dose Computed Tomography in Resource-Constrained Sites.

BACKGROUND: Existing challenges of lung cancer screening included non-accessibility of computed tomo...

[Clinical Application of "Three-Low" Technique Combined with Artificial Intelligence Iterative Reconstruction Algorithm in Aortic CT Angiography].

OBJECTIVE: To explore the application value of the "three-low" technique (low radiation dose, low co...

Application of Machine Learning Approaches to Predict Postnatal Growth Failure in Very Low Birth Weight Infants.

PURPOSE: The aims of the study were to develop and evaluate a machine learning model with which to p...

Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.

OBJECTIVE: Artificial intelligence (AI) models may propagate harmful biases in performance and hence...

Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review.

Skin cancers occur commonly worldwide. The prognosis and disease burden are highly dependent on the ...

S2Snet: deep learning for low molecular weight RNA identification with nanopore.

Ribonucleic acid (RNA) is a pivotal nucleic acid that plays a crucial role in regulating many biolog...

AggMapNet: enhanced and explainable low-sample omics deep learning with feature-aggregated multi-channel networks.

Omics-based biomedical learning frequently relies on data of high-dimensions (up to thousands) and l...

Systematic TB screening using WHO radiograph categorisation and care outcomes.

An appropriate screening approach and quality care are crucial for TB programmes in prisons. This s...

Gell-Mann-Low Criticality in Neural Networks.

Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory o...

Force and torque-free helical tail robot to study low Reynolds number micro-organism swimming.

Helical propulsion is used by many micro-organisms to swim in viscous-dominated environments. Their ...

Estimation of Low-Density Lipoprotein Cholesterol Concentration Using Machine Learning.

OBJECTIVE: Low-density lipoprotein cholesterol (LDL-C) can be estimated using the Friedewald and Mar...

Fast Improvement of TEM Images with Low-Dose Electrons by Deep Learning.

Low electron dose observation is indispensable for observing various samples using a transmission el...

First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels.

OBJECTIVE: The aim of this study was to evaluate the image quality (IQ) and performance of an artifi...

Low-dose CT noise reduction based on local total variation and improved wavelet residual CNN.

BACKGROUND: Low-dose computed tomography (LDCT) is an effective method for reducing radiation exposu...

Low Risk of Venous Thromboembolism After Robot-assisted Radical Prostatectomy Through Systemic Image Assessment: A Prospective Study.

BACKGROUND/AIM: The aim of the study was to evaluate the risk of venous thromboembolism (VTE) after ...

Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational study.

The coronavirus disease 2019 (COVID-19) epidemic went down in history as a pandemic caused by corona...

Mathematical and deep learning analysis based on tissue dielectric properties at low frequencies predict outcome in human breast cancer.

BACKGROUND: The early detection of human breast cancer represents a great chance of survival. Malign...