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 …
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 …
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 …
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 …
CO-IRv2: Optimized InceptionResNetV2 for COVID-19 detection from chest CT images
This paper focuses on the application of deep learning (DL) in the diagnosis of coronavirus
disease (COVID-19). The novelty of this work is in the introduction of optimized …
disease (COVID-19). The novelty of this work is in the introduction of optimized …
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 …
Development and validation of a hybrid deep learning–machine learning approach for severity assessment of COVID-19 and other pneumonias
Abstract The Coronavirus Disease 2019 (COVID-19) is transitioning into the endemic phase.
Nonetheless, it is crucial to remain mindful that pandemics related to infectious respiratory …
Nonetheless, it is crucial to remain mindful that pandemics related to infectious respiratory …
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 …
Hemogram‐based decision tree models for discriminating COVID‐19 from RSV in infants
D Dobrijević, L Andrijević, J Antić… - Journal of Clinical …, 2023 - Wiley Online Library
Objective Decision trees are efficient and reliable decision‐making algorithms, and
medicine has reached its peak of interest in these methods during the current pandemic …
medicine has reached its peak of interest in these methods during the current pandemic …
Machine learning-based analytics of the impact of the Covid-19 pandemic on alcohol consumption habit changes among United States healthcare workers
The COVID-19 pandemic is a global health concern that has spread around the globe.
Machine Learning is promising in the fight against the COVID-19 pandemic. Machine …
Machine Learning is promising in the fight against the COVID-19 pandemic. Machine …