AIMC Topic: Reproducibility of Results

Clear Filters Showing 3211 to 3220 of 5908 articles

Using Deep Learning to Automate Goldmann Applanation Tonometry Readings.

Ophthalmology
PURPOSE: To develop an objective and automated method for measuring intraocular pressure using deep learning and fixed-force Goldmann applanation tonometry (GAT) techniques.

Modernization of bone age assessment: comparing the accuracy and reliability of an artificial intelligence algorithm and shorthand bone age to Greulich and Pyle.

Skeletal radiology
UNLABELLED: Greulich and Pyle (GP) is one of the most common methods to determine bone age from hand radiographs. In recent years, new methods were developed to increase the efficiency in bone age analysis like the shorthand bone age (SBA) and automa...

Learning-based local-to-global landmark annotation for automatic 3D cephalometry.

Physics in medicine and biology
The annotation of three-dimensional (3D) cephalometric landmarks in 3D computerized tomography (CT) has become an essential part of cephalometric analysis, which is used for diagnosis, surgical planning, and treatment evaluation. The automation of 3D...

Detection and identification of Cannabis sativa L. using near infrared hyperspectral imaging and machine learning methods. A feasibility study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Remote identification of illegal plantations of Cannabis sativa Linnaeus is an important task for the Brazilian Federal Police. The current analytical methodology is expensive and strongly dependent on the expertise of the forensic investigator. A fa...

Neuronal mechanisms for sequential activation of memory items: Dynamics and reliability.

PloS one
In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corresponding to two different types of cerebral functions: activation of regular or irregular sequences....

Computer-Aided Detection AI Reduces Interreader Variability in Grading Hip Abnormalities With MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurate interpretation of hip MRI is time-intensive and difficult, prone to inter- and intrareviewer variability, and lacks a universally accepted grading scale to evaluate morphological abnormalities.

Deep learning assessment of breast terminal duct lobular unit involution: Towards automated prediction of breast cancer risk.

PloS one
Terminal duct lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cancer. A major bottleneck in studying TDLU involution in large cohort studie...

Differential Diagnosis of Benign and Malignant Thyroid Nodules Using Deep Learning Radiomics of Thyroid Ultrasound Images.

European journal of radiology
PURPOSE: We aimed to propose a highly automatic and objective model named deep learning Radiomics of thyroid (DLRT) for the differential diagnosis of benign and malignant thyroid nodules from ultrasound (US) images.

A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: The purpose of this study is to evaluate the performance of a novel deep learning (DL) tool for fully automated measurements of the sagittal spinopelvic balance from X-ray images of the spine in comparison with manual measurements.

Deep learning for computational structural optimization.

ISA transactions
We investigate a novel computational approach to computational structural optimization based on deep learning. After employing algorithms to solve the stiffness formulation of structures, we used their improvement to optimize the structural computati...