US Health Policy

Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach.

The electrocardiogram (ECG) is the most common tool used to predict left ventricular hypertrophy (LV...

Analysis of Drug Effects on iPSC Cardiomyocytes with Machine Learning.

Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer an attractive...

Enhancing Top-Down Proteomics Data Analysis by Combining Deconvolution Results through a Machine Learning Strategy.

Top-down mass spectrometry (MS) is a powerful tool for the identification and comprehensive characte...

Developing an Interactive Environment Through the Teaching of Mathematics with Small Robots.

The article is the product of the study "Development of innovative resources to improve logical-math...

Machine learning and the future of Medicare fraud detection.

Lessons Learned About Autonomous AI: Finding a Safe, Efficacious, and Ethical Path Through the Development Process.

Artificial intelligence (AI) describes systems capable of making decisions of high cognitive complex...

Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat with Radiofrequency Ultrasound Data Using One-dimensional Convolutional Neural Networks.

Background Radiofrequency ultrasound data from the liver contain rich information about liver micros...

Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.

BACKGROUND:  Modeling human cardiac diseases with induced pluripotent stem cells not only enables to...

Machine Learning Algorithms for Predicting the Recurrence of Stage IV Colorectal Cancer After Tumor Resection.

The aim of this study is to explore the feasibility of using machine learning (ML) technology to pre...

From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.

The radiology practice has access to a wealth of data in the radiologist information system, dictati...

Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits.

Integrated breast cancer care is complex, marked by multiple hand-offs between primary care and spec...

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making.

Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds ...

Deep Learning Models for Health and Safety Risk Prediction in Power Infrastructure Projects.

Inappropriate management of health and safety (H&S) risk in power infrastructure projects can result...

Social behavior for autonomous vehicles.

Deployment of autonomous vehicles on public roads promises increased efficiency and safety. It requi...

Energy enhanced tissue texture in spectral computed tomography for lesion classification.

Tissue texture reflects the spatial distribution of contrasts of image voxel gray levels, i.e., the ...

The low-protein diet for chronic kidney disease: 8 years of clinical experience in a nephrology ward.

BACKGROUND: Guidelines indicate that a low-protein diet (LPD) delays dialysis in severe chronic kidn...

Trust Me, I'm a Chatbot: How Artificial Intelligence in Health Care Fails the Turing Test.

Over the next decade, one issue which will dominate sociotechnical studies in health informatics is ...

Development and validation of 15-month mortality prediction models: a retrospective observational comparison of machine-learning techniques in a national sample of Medicare recipients.

OBJECTIVE: The objective is to develop and validate a predictive model for 15-month mortality using ...

Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Review.

BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligenc...

Preoperative Prediction of Value Metrics and a Patient-Specific Payment Model for Primary Total Hip Arthroplasty: Development and Validation of a Deep Learning Model.

BACKGROUND: The primary objective was to develop and test an artificial neural network (ANN) that le...

Robust optic disc and cup segmentation with deep learning for glaucoma detection.

Glaucoma is rated as the leading cause of irreversible vision loss worldwide. Early detection of gla...