Recent progress in transformer-based medical image analysis
The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
A comprehensive review on variants of SARS-CoVs-2: Challenges, solutions and open issues
SARS-CoV-2 is an infected disease caused by one of the variants of Coronavirus which
emerged in December 2019. It is declared a pandemic by WHO in March 2020. COVID-19 …
emerged in December 2019. It is declared a pandemic by WHO in March 2020. COVID-19 …
Learning size-adaptive molecular substructures for explainable drug–drug interaction prediction by substructure-aware graph neural network
Drug–drug interactions (DDIs) can trigger unexpected pharmacological effects on the body,
and the causal mechanisms are often unknown. Graph neural networks (GNNs) have been …
and the causal mechanisms are often unknown. Graph neural networks (GNNs) have been …
MGraphDTA: deep multiscale graph neural network for explainable drug–target binding affinity prediction
Predicting drug–target affinity (DTA) is beneficial for accelerating drug discovery. Graph
neural networks (GNNs) have been widely used in DTA prediction. However, existing …
neural networks (GNNs) have been widely used in DTA prediction. However, existing …
[HTML][HTML] Bilateral adaptive graph convolutional network on CT based Covid-19 diagnosis with uncertainty-aware consensus-assisted multiple instance learning
Abstract Coronavirus disease (COVID-19) has caused a worldwide pandemic, putting
millions of people's health and lives in jeopardy. Detecting infected patients early on chest …
millions of people's health and lives in jeopardy. Detecting infected patients early on chest …
Artificial intelligence to estimate the tear film breakup time and diagnose dry eye disease
E Shimizu, T Ishikawa, M Tanji, N Agata… - Scientific reports, 2023 - nature.com
The use of artificial intelligence (AI) in the diagnosis of dry eye disease (DED) remains
limited due to the lack of standardized image formats and analysis models. To overcome …
limited due to the lack of standardized image formats and analysis models. To overcome …
HCO-RLF: Hybrid classification optimization using recurrent learning and fuzzy for COVID-19 detection on CT images
COVID-19 infection detection through initial lesion classification provides early diagnosis
and prevents breathing difficulties. Detecting the infectious part of the lungs using …
and prevents breathing difficulties. Detecting the infectious part of the lungs using …
CARes‐UNet: Content‐aware residual UNet for lesion segmentation of COVID‐19 from chest CT images
Abstract Purpose Coronavirus disease 2019 (COVID‐19) has caused a serious global
health crisis. It has been proven that the deep learning method has great potential to assist …
health crisis. It has been proven that the deep learning method has great potential to assist …
[HTML][HTML] Combating COVID-19 using generative adversarial networks and artificial intelligence for medical images: sco** review
Background: Research on the diagnosis of COVID-19 using lung images is limited by the
scarcity of imaging data. Generative adversarial networks (GANs) are popular for synthesis …
scarcity of imaging data. Generative adversarial networks (GANs) are popular for synthesis …
Multi-channel based image processing scheme for pneumonia identification
Pneumonia is a prevalent severe respiratory infection that affects the distal and alveoli
airways. Across the globe, it is a serious public health issue that has caused high mortality …
airways. Across the globe, it is a serious public health issue that has caused high mortality …