AIMC Topic: Humans

Clear Filters Showing 56411 to 56420 of 95995 articles

Ankle fracture classification using deep learning: automating detailed AO Foundation/Orthopedic Trauma Association (AO/OTA) 2018 malleolar fracture identification reaches a high degree of correct classification.

Acta orthopaedica
Background and purpose - Classification of ankle fractures is crucial for guiding treatment but advanced classifications such as the AO Foundation/Orthopedic Trauma Association (AO/OTA) are often too complex for human observers to learn and use. We h...

Super-Resolved q-Space deep learning with uncertainty quantification.

Medical image analysis
Diffusion magnetic resonance imaging (dMRI) provides a noninvasive method for measuring brain tissue microstructure. q-Space deep learning(q-DL) methods have been developed to accurately estimate tissue microstructure from dMRI scans acquired with a ...

Advanced Imaging and Sampling in Barrett's Esophagus: Artificial Intelligence to the Rescue?

Gastrointestinal endoscopy clinics of North America
Because the current Barrett's esophagus (BE) surveillance protocol suffers from sampling error of random biopsies and a high miss-rate of early neoplastic lesions, many new endoscopic imaging and sampling techniques have been developed. None of these...

Deep-learning-based segmentation of the vocal tract and articulators in real-time magnetic resonance images of speech.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Magnetic resonance (MR) imaging is increasingly used in studies of speech as it enables non-invasive visualisation of the vocal tract and articulators, thus providing information about their shape, size, motion and position....

Incorporating historical sub-optimal deep neural networks for dose prediction in radiotherapy.

Medical image analysis
As the main treatment for cancer patients, radiotherapy has achieved enormous advancement over recent decades. However, these achievements have come at the cost of increased treatment plan complexity, necessitating high levels of expertise experience...

Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic.

Healthcare (Amsterdam, Netherlands)
The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation ...

A primer for understanding radiology articles about machine learning and deep learning.

Diagnostic and interventional imaging
The application of machine learning and deep learning in the field of imaging is rapidly growing. Although the principles of machine and deep learning are unfamiliar to the majority of clinicians, the basics are not so complicated. One of the major i...

Using deep learning to model the biological dose prediction on bulky lung cancer patients of partial stereotactic ablation radiotherapy.

Medical physics
PURPOSE: To develop a biological dose prediction model considering tissue bio-reactions in addition to patient anatomy for achieving a more comprehensive evaluation of tumor control and promoting the automatic planning of bulky lung cancer.

COSMO-RS-Based Descriptors for the Machine Learning-Enabled Screening of Nucleotide Analogue Drugs against SARS-CoV-2.

The journal of physical chemistry letters
Chemical similarity-based approaches employed to repurpose or develop new treatments for emerging diseases, such as COVID-19, correlates molecular structure-based descriptors of drugs with those of a physiological counterpart or clinical phenotype. W...

Federated Learning on Clinical Benchmark Data: Performance Assessment.

Journal of medical Internet research
BACKGROUND: Federated learning (FL) is a newly proposed machine-learning method that uses a decentralized dataset. Since data transfer is not necessary for the learning process in FL, there is a significant advantage in protecting personal privacy. T...