AIMC Topic: Models, Theoretical

Clear Filters Showing 641 to 650 of 1953 articles

Natural language processing was effective in assisting rapid title and abstract screening when updating systematic reviews.

Journal of clinical epidemiology
BACKGROUND AND OBJECTIVE: To examine whether the use of natural language processing (NLP) technology is effective in assisting rapid title and abstract screening when updating a systematic review.

Artificial immune system features added to breast cancer clinical data for machine learning (ML) applications.

Bio Systems
We here propose a new method of combining a mathematical model that describes a chemotherapy treatment for breast cancer with a machine-learning (ML) algorithm to increase performance in predicting tumor size using a five-step procedure. The first st...

A comparison of the value of two machine learning predictive models to support bovine tuberculosis disease control in England.

Preventive veterinary medicine
Nearly a decade into Defra's current eradication strategy, bovine tuberculosis (bTB) remains a serious animal health problem in England, with c.30,000 cattle slaughtered annually in the fight against this insidious disease. There is an urgent need to...

Modelization of Covid-19 pandemic spreading: A machine learning forecasting with relaxation scenarios of countermeasures.

Journal of infection and public health
BACKGROUND & OBJECTIVE: Mathematical modeling is the most scientific technique to understand the evolution of natural phenomena, including the spread of infectious diseases. Therefore, these modeling tools have been widely used in epidemiology for pr...

In silico prediction of chemical acute contact toxicity on honey bees via machine learning methods.

Toxicology in vitro : an international journal published in association with BIBRA
In recent years, the decline of honey bees and the collapse of bee colonies have caught the attention of ecologists, and the use of pesticides is one of the main reasons for the decline. Therefore, ecological risk assessment of pesticides is essentia...

An artificial neural network based mathematical model for a stochastic health care facility location problem.

Health care management science
This research is conducted to investigate the problem of locating the trauma centers and helicopters' station in order to optimize the trauma care system. The stochastic characteristics of the system, such as stochastic transferring time of the patie...

Extended Robust Exponential Stability of Fuzzy Switched Memristive Inertial Neural Networks With Time-Varying Delays on Mode-Dependent Destabilizing Impulsive Control Protocol.

IEEE transactions on neural networks and learning systems
This article investigates the problem of robust exponential stability of fuzzy switched memristive inertial neural networks (FSMINNs) with time-varying delays on mode-dependent destabilizing impulsive control protocol. The memristive model presented ...

Continual Multiview Task Learning via Deep Matrix Factorization.

IEEE transactions on neural networks and learning systems
The state-of-the-art multitask multiview (MTMV) learning tackles a scenario where multiple tasks are related to each other via multiple shared feature views. However, in many real-world scenarios where a sequence of the multiview task comes, the high...

The Prediction of Hepatitis E through Ensemble Learning.

International journal of environmental research and public health
According to the World Health Organization, about 20 million people are infected with Hepatitis E every year. In 2015, there were 44,000 deaths due to HEV infection worldwide. Food, water and climate are key factors that affect the outbreak of Hepati...

DeepDILI: Deep Learning-Powered Drug-Induced Liver Injury Prediction Using Model-Level Representation.

Chemical research in toxicology
Drug-induced liver injury (DILI) is the most frequently reported single cause of safety-related withdrawal of marketed drugs. It is essential to identify drugs with DILI potential at the early stages of drug development. In this study, we describe a ...