Machine learning and deep learning in smart manufacturing: The smart grid paradigm
Industry 4.0 is the new industrial revolution. By connecting every machine and activity
through network sensors to the Internet, a huge amount of data is generated. Machine …
through network sensors to the Internet, a huge amount of data is generated. Machine …
A systematic survey of computer-aided diagnosis in medicine: Past and present developments
J Yanase, E Triantaphyllou - Expert Systems with Applications, 2019 - Elsevier
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort
expended in the interface of medicine and computer science. As some CAD systems in …
expended in the interface of medicine and computer science. As some CAD systems in …
[HTML][HTML] Comparing different supervised machine learning algorithms for disease prediction
Supervised machine learning algorithms have been a dominant method in the data mining
field. Disease prediction using health data has recently shown a potential application area …
field. Disease prediction using health data has recently shown a potential application area …
Transfer learning with convolutional neural networks for classification of abdominal ultrasound images
PM Cheng, HS Malhi - Journal of digital imaging, 2017 - Springer
The purpose of this study is to evaluate transfer learning with deep convolutional neural
networks for the classification of abdominal ultrasound images. Grayscale images from 185 …
networks for the classification of abdominal ultrasound images. Grayscale images from 185 …
Lung texture in serial thoracic computed tomography scans: correlation of radiomics-based features with radiation therapy dose and radiation pneumonitis …
Purpose To assess the relationship between radiation dose and change in a set of
mathematical intensity-and texture-based features and to determine the ability of texture …
mathematical intensity-and texture-based features and to determine the ability of texture …
Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas
Purpose To retrospectively investigate the value of computerized three-dimensional texture
analysis for differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas …
analysis for differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas …
Methods Used in Computer‐Aided Diagnosis for Breast Cancer Detection Using Mammograms: A Review
SZ Ramadan - Journal of healthcare engineering, 2020 - Wiley Online Library
According to the American Cancer Society's forecasts for 2019, there will be about 268,600
new cases in the United States with invasive breast cancer in women, about 62,930 new …
new cases in the United States with invasive breast cancer in women, about 62,930 new …
Clinical prediction rules
ST Adams, SH Leveson - Bmj, 2012 - bmj.com
Clinical prediction rules are mathematical tools that are intended to guide clinicians in their
everyday decision making. The popularity of such rules has increased greatly over the past …
everyday decision making. The popularity of such rules has increased greatly over the past …
Overview of artificial neural network models in the biomedical domain.
V Renganathan - Bratislava Medical Journal/Bratislavské …, 2019 - search.ebscohost.com
AIM: The aim of this paper is to provide an overview of artifi cial neural network (ANN) in
biomedical domain and compare it with the logistic regression model. METHODS: Artifi cial …
biomedical domain and compare it with the logistic regression model. METHODS: Artifi cial …
A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones
Background Undernutrition is the main cause of child death in developing countries. This
paper aimed to explore the efficacy of machine learning (ML) approaches in predicting …
paper aimed to explore the efficacy of machine learning (ML) approaches in predicting …