[HTML][HTML] A systematic review on artificial intelligence techniques for detecting thyroid diseases
The use of artificial intelligence approaches in health-care systems has grown rapidly over
the last few years. In this context, early detection of diseases is the most common area of …
the last few years. In this context, early detection of diseases is the most common area of …
Real-time abnormal object detection for video surveillance in smart cities
With the adaptation of video surveillance in many areas for object detection, monitoring
abnormal behavior in several cameras requires constant human tracking for a single camera …
abnormal behavior in several cameras requires constant human tracking for a single camera …
A holistic approach to identify and classify COVID-19 from chest radiographs, ECG, and CT-scan images using shufflenet convolutional neural network
Early and precise COVID-19 identification and analysis are pivotal in reducing the spread of
COVID-19. Medical imaging techniques, such as chest X-ray or chest radiographs …
COVID-19. Medical imaging techniques, such as chest X-ray or chest radiographs …
[HTML][HTML] Ensemble deep learning derived from transfer learning for classification of COVID-19 patients on hybrid deep-learning-based lung segmentation: a data …
AK Dubey, GL Chabert, A Carriero, A Pasche… - Diagnostics, 2023 - mdpi.com
Background and motivation: Lung computed tomography (CT) techniques are high-
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
Design of type-3 fuzzy systems and ensemble neural networks for COVID-19 time series prediction using a firefly algorithm
In this work, information on COVID-19 confirmed cases is utilized as a dataset to perform
time series predictions. We propose the design of ensemble neural networks (ENNs) and …
time series predictions. We propose the design of ensemble neural networks (ENNs) and …
Internet of medical things-based COVID-19 detection in CT images fused with fuzzy ensemble and transfer learning models
One of the most difficult research areas in today's healthcare industry to combat the
coronavirus pandemic is accurate COVID-19 detection. Because of its low infection miss rate …
coronavirus pandemic is accurate COVID-19 detection. Because of its low infection miss rate …
Ensemble classification of integrated CT scan datasets in detecting COVID-19 using feature fusion from contourlet transform and CNN
The COVID-19 disease caused by coronavirus is constantly changing due to the emergence
of different variants and thousands of people are dying every day worldwide. Early detection …
of different variants and thousands of people are dying every day worldwide. Early detection …
Generalizability assessment of COVID-19 3D CT data for deep learning-based disease detection
Background Artificial intelligence technologies in classification/detection of COVID-19
positive cases suffer from generalizability. Moreover, accessing and preparing another large …
positive cases suffer from generalizability. Moreover, accessing and preparing another large …
Detection of COVID‐19 Case from Chest CT Images Using Deformable Deep Convolutional Neural Network
The infectious coronavirus disease (COVID‐19) has become a great threat to global human
health. Timely and rapid detection of COVID‐19 cases is very crucial to control its spreading …
health. Timely and rapid detection of COVID‐19 cases is very crucial to control its spreading …
Evolutionary Machine Learning in Medicine
MA Lones, SL Smith - Handbook of Evolutionary Machine Learning, 2023 - Springer
This chapter reviews applications of evolutionary machine learning within the medical
domain. It is divided into three parts. The first two parts give examples of recent work in two …
domain. It is divided into three parts. The first two parts give examples of recent work in two …