[HTML][HTML] Application of explainable artificial intelligence in medical health: A systematic review of interpretability methods

SS Band, A Yarahmadi, CC Hsu, M Biyari… - Informatics in Medicine …, 2023 - Elsevier
This paper investigates the applications of explainable AI (XAI) in healthcare, which aims to
provide transparency, fairness, accuracy, generality, and comprehensibility to the results …

Data-driven analytics leveraging artificial intelligence in the era of COVID-19: an insightful review of recent developments

A Majeed, SO Hwang - Symmetry, 2021 - mdpi.com
This paper presents the role of artificial intelligence (AI) and other latest technologies that
were employed to fight the recent pandemic (ie, novel coronavirus disease-2019 (COVID …

Chest X-ray classification for the detection of COVID-19 using deep learning techniques

E Khan, MZU Rehman, F Ahmed, FA Alfouzan… - Sensors, 2022 - mdpi.com
Recent technological developments pave the path for deep learning-based techniques to be
used in almost every domain of life. The precision of deep learning techniques make it …

Design and analysis of a deep learning ensemble framework model for the detection of COVID-19 and pneumonia using large-scale CT scan and X-ray image …

X Xue, S Chinnaperumal, GM Abdulsahib, RR Manyam… - Bioengineering, 2023 - mdpi.com
Recently, various methods have been developed to identify COVID-19 cases, such as PCR
testing and non-contact procedures such as chest X-rays and computed tomography (CT) …

RADIC: A tool for diagnosing COVID-19 from chest CT and X-ray scans using deep learning and quad-radiomics

O Attallah - Chemometrics and Intelligent Laboratory Systems, 2023 - Elsevier
Deep learning (DL) algorithms have demonstrated a high ability to perform speedy and
accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The …

A Hybrid Deep Learning CNN model for COVID-19 detection from chest X-rays

M Abdullah, F berhe Abrha, B Kedir, TT Tagesse - Heliyon, 2024 - cell.com
Abstract Coronavirus disease (COVID-2019) is emerging in Wuhan, China in 2019. It has
spread throughout the world since the year 2020. Millions of people were affected and …

RVCNet: A hybrid deep neural network framework for the diagnosis of lung diseases

FB Alam, P Podder, MRH Mondal - Plos one, 2023 - journals.plos.org
Early evaluation and diagnosis can significantly reduce the life-threatening nature of lung
diseases. Computer-aided diagnostic systems (CADs) can help radiologists make more …

Rethinking densely connected convolutional networks for diagnosing infectious diseases

P Podder, FB Alam, MRH Mondal, MJ Hasan, A Rohan… - Computers, 2023 - mdpi.com
Due to its high transmissibility, the COVID-19 pandemic has placed an unprecedented
burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a …

Attention guided grad-CAM: an improved explainable artificial intelligence model for infrared breast cancer detection

K Raghavan, K v - Multimedia Tools and Applications, 2024 - Springer
Explainable artificial intelligence (XAI) can help build trust between AI models and
healthcare professionals in the context of medical image classification. XAI can help explain …

RETRACTED ARTICLE: FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices

K Ahmad, MS Khan, F Ahmed, M Driss, W Boulila… - Fire Ecology, 2023 - Springer
Background Forests cover nearly one-third of the Earth's land and are some of our most
biodiverse ecosystems. Due to climate change, these essential habitats are endangered by …