AIMC Topic: Prevalence
Clear Filters Showing 101 to 110 of 280 articles
Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition.
Scientific reports
Nov 1, 2021
In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), cal...
Perception of yips among professional Japanese golfers: perspectives from a network modelled approach.
Scientific reports
Oct 11, 2021
'Yips' in golf is a complex spectrum of anxiety and movement-disorder that affects competitive sporting performance. With unclear etiology and high prevalence documented in western literature, the perception and management of this psycho-neuromuscula...
Efficient and targeted COVID-19 border testing via reinforcement learning.
Nature
Sep 22, 2021
Throughout the coronavirus disease 2019 (COVID-19) pandemic, countries have relied on a variety of ad hoc border control protocols to allow for non-essential travel while safeguarding public health, from quarantining all travellers to restricting ent...
A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.
The American journal of tropical medicine and hygiene
Sep 20, 2021
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...
Early Diagnosis
Spain
Emigrants and Immigrants
Asia
Child
Models, Theoretical
Mexico
Mass Screening
South America
Central America
Communicable Diseases, Imported
Cross-Sectional Studies
Male
Middle Aged
Infant
Prevalence
Africa
Adolescent
Child, Preschool
Aged
Aged, 80 and over
Young Adult
Adult
Humans
Retrospective Studies
Machine Learning
Female
Infant, Newborn
Multivariate random forest prediction of poverty and malnutrition prevalence.
PloS one
Sep 8, 2021
Advances in remote sensing and machine learning enable increasingly accurate, inexpensive, and timely estimation of poverty and malnutrition indicators to guide development and humanitarian agencies' programming. However, state of the art models ofte...
Deep Learning-Based Natural Language Processing in Radiology: The Impact of Report Complexity, Disease Prevalence, Dataset Size, and Algorithm Type on Model Performance.
Journal of medical systems
Sep 4, 2021
In radiology, natural language processing (NLP) allows the extraction of valuable information from radiology reports. It can be used for various downstream tasks such as quality improvement, epidemiological research, and monitoring guideline adherenc...
Detection of subclinical rheumatic heart disease in children using a deep learning algorithm on digital stethoscope: a study protocol.
BMJ open
Aug 5, 2021
INTRODUCTION: Rheumatic heart diseases (RHDs) contribute significant morbidity and mortality globally. To reduce the burden of RHD, timely initiation of secondary prophylaxis is important. The objectives of this study are to determine the frequency o...
The cardiovascular phenotype of Chronic Obstructive Pulmonary Disease (COPD): Applying machine learning to the prediction of cardiovascular comorbidities.
Respiratory medicine
Jul 7, 2021
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous group of lung conditions that are challenging to diagnose and treat. As the presence of comorbidities often exacerbates this scenario, the characterization of patients with C...
[Artificial Intelligence in epidemiology].
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Jun 20, 2021
Artificial Intelligence can be leveraged to analyze great amounts of data. It can be used on images or textual data to define the epidemiology of diseases, such as cancer. In this review, we will present and discuss the applications of AI in this set...
Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index.
Environmental pollution (Barking, Essex : 1987)
Jun 14, 2021
Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood asthma. The aim of this study was to use a novel greenness exposure assessment method, capable of o...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823