AIMC Topic: Reproducibility of Results

Clear Filters Showing 3811 to 3820 of 5908 articles

Machine learning for detecting moyamoya disease in plain skull radiography using a convolutional neural network.

EBioMedicine
BACKGROUND: Recently, innovative attempts have been made to identify moyamoya disease (MMD) by focusing on the morphological differences in the head of MMD patients. Following the recent revolution in the development of deep learning (DL) algorithms,...

Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk.

BMC medical research methodology
BACKGROUND: The use of Cardiovascular Disease (CVD) risk estimation scores in primary prevention has long been established. However, their performance still remains a matter of concern. The aim of this study was to explore the potential of using ML m...

Automated, machine learning-based, 3D echocardiographic quantification of left ventricular mass.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND: Although 3D echocardiography (3DE) circumvents many limitations of 2D echocardiography by allowing direct measurements of left ventricular (LV) mass, it is seldom used in clinical practice due to time-consuming analysis. A recently develo...

Using natural language processing and machine learning to identify breast cancer local recurrence.

BMC bioinformatics
BACKGROUND: Identifying local recurrences in breast cancer from patient data sets is important for clinical research and practice. Developing a model using natural language processing and machine learning to identify local recurrences in breast cance...

Human/robotic interaction: vision limits performance in simulated vitreoretinal surgery.

Acta ophthalmologica
PURPOSE: Compare accuracy and precision in XYZ of stationary and dynamic tasks performed by surgeons with and without the use of a tele-operated robotic micromanipulator in a simulated vitreoretinal environment. The tasks were performed using a surgi...

Reliable Label-Efficient Learning for Biomedical Image Recognition.

IEEE transactions on bio-medical engineering
The use of deep neural networks for biomedical image analysis requires a sufficient number of labeled datasets. To acquire accurate labels as the gold standard, multiple observers with specific expertise are required for both annotation and proofread...

Molecularly imprinted polymer based quartz crystal microbalance sensor for the clinical detection of insulin.

Materials science & engineering. C, Materials for biological applications
In this study, quartz crystal microbalance sensors based on molecular imprinting technology were fabricated for real-time detection of insulin in aqueous solution and artificial plasma. This study describes the preparation of insulin imprinted poly(h...

Employing AgNPs doped amidoxime-modified polyacrylonitrile (PAN-oxime) nanofibers for target induced strand displacement-based electrochemical aptasensing of CA125 in ovarian cancer patients.

Materials science & engineering. C, Materials for biological applications
In this study, a high-performance biosensing nanoplatform based on amidoxime-modified polyacrylonitrile nanofibers decorated with Ag nanoparticles (AgNPs-PAN-oxime NFs) is described. The AgNPs-PAN-oxime NFs were prepared by the combination of electro...

Development and Validation of a Machine Learning Algorithm After Primary Total Hip Arthroplasty: Applications to Length of Stay and Payment Models.

The Journal of arthroplasty
BACKGROUND: Value-based payment programs in orthopedics, specifically primary total hip arthroplasty (THA), present opportunities to apply forecasting machine learning techniques to adjust payment models to a specific patient or population. The objec...

Integrating camera imagery, crowdsourcing, and deep learning to improve high-frequency automated monitoring of snow at continental-to-global scales.

PloS one
Snow is important for local to global climate and surface hydrology, but spatial and temporal heterogeneity in the extent of snow cover make accurate, fine-scale mapping and monitoring of snow an enormous challenge. We took 184,453 daily near-surface...