US Health Policy

Latest AI and machine learning research in us health policy for healthcare professionals.

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Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions.

OBJECTIVES: We aimed to assess the performance of radiomics and machine learning (ML) for classifica...

Prognostic Value of Pulmonary Transit Time and Pulmonary Blood Volume Estimation Using Myocardial Perfusion CMR.

OBJECTIVES: The purpose of this study was to explore the prognostic significance of PTT and PBVi usi...

Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms.

Patients with rare conditions such as cardiac amyloidosis (CA) are difficult to identify, given the ...

A machine learning approach to screen for preclinical Alzheimer's disease.

Combining multimodal biomarkers could help in the early diagnosis of Alzheimer's disease (AD). We in...

Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray dataset.

The reliability of machine learning models can be compromised when trained on low quality data. Many...

Core services that power AI-driven transformation in cancer research and care.

This review captures some key lessons learned in the course of helping some of America's leading hea...

The Value of Surgical Data-Impact on the Future of the Surgical Field.

The combination of computing power, connectivity, and big data has been touted as the future of inno...

A win-win situation: Does familiarity with a social robot modulate feedback monitoring and learning?

Social species rely on the ability to modulate feedback-monitoring in social contexts to adjust one'...

Quality gaps in public pancreas imaging datasets: Implications & challenges for AI applications.

OBJECTIVE: Quality gaps in medical imaging datasets lead to profound errors in experiments. Our obje...

[Artificial intelligence in psychiatry: predictive value of characteristics on MR imaging of the brain].

The clinical application of neuroimaging for psychological complaints has so far been limited to the...

"When they say weed causes depression, but it's your fav antidepressant": Knowledge-aware attention framework for relationship extraction.

With the increasing legalization of medical and recreational use of cannabis, more research is neede...

Enhancement of nutritional value of fried fish using an artificial intelligence approach.

Frying affects the nutritional quality of fish detrimentally. In this study, using Catla catla and m...

Generalizability of deep learning models for dental image analysis.

We assessed the generalizability of deep learning models and how to improve it. Our exemplary use-ca...

Software Defect Prediction for Healthcare Big Data: An Empirical Evaluation of Machine Learning Techniques.

Software defect prediction (SDP) in the initial period of the software development life cycle (SDLC)...

Using Machine Learning to Unravel the Value of Radiographic Features for the Classification of Bone Tumors.

OBJECTIVES: To build and validate random forest (RF) models for the classification of bone tumors ba...

Robotic Prostatectomy and Prostate Cancer-Related Medicaid Spending: Evidence from New York State.

BACKGROUND: Robotic prostatectomy is a costly new technology, but the costs may be offset by changes...

Weakly supervised deep learning for determining the prognostic value of F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type.

PURPOSE: To develop a weakly supervised deep learning (WSDL) method that could utilize incomplete/mi...

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