AI Medical Compendium Topic:
Time Factors

Clear Filters Showing 841 to 850 of 1871 articles

Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed.

Journal of medical Internet research
BACKGROUND: Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing i...

A fast deep learning approach for beam orientation optimization for prostate cancer treated with intensity-modulated radiation therapy.

Medical physics
PURPOSE: Beam orientation selection, whether manual or protocol-based, is the current clinical standard in radiation therapy treatment planning, but it is tedious and can yield suboptimal results. Many algorithms have been designed to optimize beam o...

Exponential and adaptive synchronization of inertial complex-valued neural networks: A non-reduced order and non-separation approach.

Neural networks : the official journal of the International Neural Network Society
This paper mainly deals with the problem of exponential and adaptive synchronization for a type of inertial complex-valued neural networks via directly constructing Lyapunov functionals without utilizing standard reduced-order transformation for iner...

Application of machine learning to predict monomer retention of therapeutic proteins after long term storage.

International journal of pharmaceutics
An important aspect of initial developability assessments as well formulation development and selection of therapeutic proteins is the evaluation of data obtained under accelerated stress condition, i.e. at elevated temperatures. We propose the appli...

Prediction of progression from pre-diabetes to diabetes: Development and validation of a machine learning model.

Diabetes/metabolism research and reviews
AIMS: Identification, a priori, of those at high risk of progression from pre-diabetes to diabetes may enable targeted delivery of interventional programmes while avoiding the burden of prevention and treatment in those at low risk. We studied whethe...

Prediction of blood pressure variability using deep neural networks.

International journal of medical informatics
PURPOSE: The purpose of our study was to predict blood pressure variability from time-series data of blood pressure measured at home and data obtained through medical examination at a hospital. Previous studies have reported the blood pressure variab...

Spacial sampled-data control for H output synchronization of directed coupled reaction-diffusion neural networks with mixed delays.

Neural networks : the official journal of the International Neural Network Society
This work investigates the H output synchronization (HOS) of the directed coupled reaction-diffusion (R-D) neural networks (NNs) with mixed delays. Firstly, a model of the directed state coupled R-D NNs is introduced, which not only contains some dis...

A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we derive a new fixed-time stability theorem based on definite integral, variable substitution and some inequality techniques. The fixed-time stability criterion and the upper bound estimate formula for the settling time are different ...

Automated tracheal intubation in an airway manikin using a robotic endoscope: a proof of concept study.

Anaesthesia
Robotic endoscope-automated via laryngeal imaging for tracheal intubation (REALITI) has been developed to enable automated tracheal intubation. This proof-of-concept study using a convenience sample of participants, comprised of trained anaesthetists...

Are All Deep Learning Architectures Alike for Point-of-Care Ultrasound?: Evidence From a Cardiac Image Classification Model Suggests Otherwise.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Little is known about optimal deep learning (DL) approaches for point-of-care ultrasound (POCUS) applications. We compared 6 popular DL architectures for POCUS cardiac image classification to determine whether an optimal DL architecture e...