A review on explainable artificial intelligence for healthcare: why, how, and when?
S Bharati, MRH Mondal… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Artificial intelligence (AI) models are increasingly finding applications in the field of
medicine. Concerns have been raised about the explainability of the decisions that are …
medicine. Concerns have been raised about the explainability of the decisions that are …
Artificial intelligence and internet of things (AI-IoT) technologies in response to COVID-19 pandemic: A systematic review
The origin of the COVID-19 pandemic has given overture to redirection, as well as
innovation to many digital technologies. Even after the progression of vaccination efforts …
innovation to many digital technologies. Even after the progression of vaccination efforts …
Lddnet: a deep learning framework for the diagnosis of infectious lung diseases
This paper proposes a new deep learning (DL) framework for the analysis of lung diseases,
including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This …
including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This …
Federated learning: Applications, challenges and future directions
Federated learning (FL) refers to a system in which a central aggregator coordinates the
efforts of several clients to solve the issues of machine learning. This setting allows the …
efforts of several clients to solve the issues of machine learning. This setting allows the …
AI‐Assisted Tuberculosis Detection and Classification from Chest X‐Rays Using a Deep Learning Normalization‐Free Network Model
Tuberculosis (TB) is an airborne disease caused by Mycobacterium tuberculosis. It is
imperative to detect cases of TB as early as possible because if left untreated, there is a 70 …
imperative to detect cases of TB as early as possible because if left untreated, there is a 70 …
Machine and deep learning for iot security and privacy: applications, challenges, and future directions
The integration of the Internet of Things (IoT) connects a number of intelligent devices with
minimum human interference that can interact with one another. IoT is rapidly emerging in …
minimum human interference that can interact with one another. IoT is rapidly emerging in …
Fled-block: Federated learning ensembled deep learning blockchain model for covid-19 prediction
R Durga, E Poovammal - Frontiers in Public Health, 2022 - frontiersin.org
With the SARS-CoV-2's exponential growth, intelligent and constructive practice is required
to diagnose the COVID-19. The rapid spread of the virus and the shortage of reliable testing …
to diagnose the COVID-19. The rapid spread of the virus and the shortage of reliable testing …
Explainable artificial intelligence (XAI) with IoHT for smart healthcare: A review
Discussing the use of artificial intelligence (AI) in healthcare, explainability is a highly
contentious topic. AI-powered systems may be superior at certain analytical tasks, but their …
contentious topic. AI-powered systems may be superior at certain analytical tasks, but their …
Deep learning for medical image registration: A comprehensive review
Image registration is a critical component in the applications of various medical image
analyses. In recent years, there has been a tremendous surge in the development of deep …
analyses. In recent years, there has been a tremendous surge in the development of deep …
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 …
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …