Weakly supervised machine learning

Z Ren, S Wang, Y Zhang - CAAI Transactions on Intelligence …, 2023 - Wiley Online Library
Supervised learning aims to build a function or model that seeks as many mappings as
possible between the training data and outputs, where each training data will predict as a …

COVID-19 in the age of artificial intelligence: a comprehensive review

J Rasheed, A Jamil, AA Hameed, F Al-Turjman… - Interdisciplinary …, 2021 - Springer
The recent COVID-19 pandemic, which broke at the end of the year 2019 in Wuhan, China,
has infected more than 98.52 million people by today (January 23, 2021) with over 2.11 …

Recurrent neural network and reinforcement learning model for COVID-19 prediction

RL Kumar, F Khan, S Din, SS Band, A Mosavi… - Frontiers in public …, 2021 - frontiersin.org
Detection and prediction of the novel Coronavirus present new challenges for the medical
research community due to its widespread across the globe. Methods driven by Artificial …

COVID-19 detection based on image regrouping and ResNet-SVM using chest X-ray images

C Zhou, J Song, S Zhou, Z Zhang, J Xing - Ieee Access, 2021 - ieeexplore.ieee.org
As the COVID-19 spread worldwide, countries around the world are actively taking
measures to fight against the epidemic. To prevent the spread of it, a high sensitivity and …

Machine learning-based research for COVID-19 detection, diagnosis, and prediction: A survey

Y Meraihi, AB Gabis, S Mirjalili, A Ramdane-Cherif… - SN computer …, 2022 - Springer
The year 2020 experienced an unprecedented pandemic called COVID-19, which impacted
the whole world. The absence of treatment has motivated research in all fields to deal with it …

Detection of COVID-19 using deep learning techniques and cost effectiveness evaluation: a survey

MK MV, S Atalla, N Almuraqab… - Frontiers in Artificial …, 2022 - frontiersin.org
Graphical-design-based symptomatic techniques in pandemics perform a quintessential
purpose in screening hit causes that comparatively render better outcomes amongst the …

Deep learning based diagnosis of COVID-19 using chest CT-scan images

T Anwar, S Zakir - 2020 IEEE 23rd international multitopic …, 2020 - ieeexplore.ieee.org
The Coronavirus disease (COVID-19) is an infectious disease that primarily affects lungs.
This virus has spread in almost every continent. Countries are racing to slow down the …

The COVID-19 epidemic analysis and diagnosis using deep learning: A systematic literature review and future directions

A Heidari, NJ Navimipour, M Unal, S Toumaj - Computers in biology and …, 2022 - Elsevier
Abstract Since December 2019, the COVID-19 outbreak has resulted in countless deaths
and has harmed all facets of human existence. COVID-19 has been designated an epidemic …

A systematic review on deep structured learning for COVID-19 screening using chest CT from 2020 to 2022

KC Santosh, D GhoshRoy, S Nakarmi - Healthcare, 2023 - mdpi.com
The emergence of the COVID-19 pandemic in Wuhan in 2019 led to the discovery of a novel
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …

SuFMoFPA: A superpixel and meta-heuristic based fuzzy image segmentation approach to explicate COVID-19 radiological images

S Chakraborty, K Mali - Expert Systems with Applications, 2021 - Elsevier
Coronavirus disease 2019 or COVID-19 is one of the biggest challenges which are being
faced by mankind. Researchers are continuously trying to discover a vaccine or medicine for …