AIMC Topic: Time Factors

Clear Filters Showing 1161 to 1170 of 2001 articles

Temporal separation of Cerenkov radiation and scintillation using artificial neural networks in Clinical LINACs.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The irradiation of scintillator-fiber optic dosimeters by clinical LINACs results in the measurement of scintillation and Cerenkov radiation. In scintillator-fiber optic dosimetry, the scintillation and Cerenkov radiation responses are separated to d...

CaSTLe - Classification of single cells by transfer learning: Harnessing the power of publicly available single cell RNA sequencing experiments to annotate new experiments.

PloS one
Single-cell RNA sequencing (scRNA-seq) is an emerging technology for profiling the gene expression of thousands of cells at the single cell resolution. Currently, the labeling of cells in an scRNA-seq dataset is performed by manually characterizing c...

Medical Image Quality Assessment Using CSO Based Deep Neural Network.

Journal of medical systems
This manuscript proposed a hybrid method of Deep Neural Network (DNN) and Cuckoo Search Optimization (CSO) with No-Reference Image Quality Assessment (NR-IQA) for achieving high accuracy, low computational complexity, flexibility and etc. of a medica...

Early Expression Detection via Online Multi-Instance Learning With Nonlinear Extension.

IEEE transactions on neural networks and learning systems
Video-based facial expression recognition has received substantial attention over the past decade, while early expression detection (EED) is still a relatively new and challenging problem. The goal of EED is to identify an expression as quickly as po...

Reachable set estimation for Markovian jump neural networks with time-varying delay.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the reachable set estimation for Markovian jump neural networks with time-varying delay and bounded peak inputs. The objective is to find a description of a reachable set that is containing all reachable states starting f...

An improved stability result for delayed Takagi-Sugeno fuzzy Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
This work proposes a novel and improved delay independent global asymptotic stability criterion for delayed Takagi-Sugeno (T-S) fuzzy Cohen-Grossberg neural networks exploiting a suitable fuzzy-type Lyapunov functional in the presence of the nondecre...

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.

Methods of information in medicine
BACKGROUND: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains a paucity of performant clinical decision support systems. For example, in the intensive care unit (...

The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control.

PloS one
In this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampled-data control. We use the input delay method to turn the sampling system into...

A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis.

Medicina intensiva
INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quickly. The severity of illness scores used are intended to be applicable to all patient populations, and generally evaluate in-hospital mortality. Howev...

Identifying Suitable Brain Regions and Trial Size Segmentation for Positive/Negative Emotion Recognition.

International journal of neural systems
The development of suitable EEG-based emotion recognition systems has become a main target in the last decades for Brain Computer Interface applications (BCI). However, there are scarce algorithms and procedures for real-time classification of emotio...