Using artificial intelligence to analyse the retinal vascular network: the future of cardiovascular risk assessment based on oculomics? A narrative review
L Arnould, F Meriaudeau, C Guenancia… - Ophthalmology and …, 2023 - Springer
The healthcare burden of cardiovascular diseases remains a major issue worldwide.
Understanding the underlying mechanisms and improving identification of people with a …
Understanding the underlying mechanisms and improving identification of people with a …
TGM-Nets: A deep learning framework for enhanced forecasting of tumor growth by integrating imaging and modeling
Prediction and uncertainty quantification of tumor progression are vital in clinical practice, ie,
disease prognosis and decision-making on treatment strategies. In this work, we propose …
disease prognosis and decision-making on treatment strategies. In this work, we propose …
Pearls and Pitfalls of Adaptive Optics Ophthalmoscopy in Inherited Retinal Diseases
Adaptive optics (AO) retinal imaging enables individual photoreceptors to be visualized in
the clinical setting. AO imaging can be a powerful clinical tool for detecting photoreceptor …
the clinical setting. AO imaging can be a powerful clinical tool for detecting photoreceptor …
Artificial to spiking neural networks conversion for scientific machine learning
We introduce a method to convert Physics-Informed Neural Networks (PINNs), commonly
used in scientific machine learning, to Spiking Neural Networks (SNNs), which are expected …
used in scientific machine learning, to Spiking Neural Networks (SNNs), which are expected …
A deep learning model for efficient end-to-end stratification of thrombotic risk in left atrial appendage
Clot formation in the left atrial appendage (LAA) poses a high risk of ischemic strokes and
systemic embolism to patients with atrial fibrillation (AF), the most common type of sustained …
systemic embolism to patients with atrial fibrillation (AF), the most common type of sustained …
A deep neural network for operator learning enhanced by attention and gating mechanisms for long-time forecasting of tumor growth
Forecasting tumor progression and assessing the uncertainty of predictions play a crucial
role in clinical settings, especially for determining disease outlook and making informed …
role in clinical settings, especially for determining disease outlook and making informed …
Deep learning for few-shot white blood cell image classification and feature learning
Differential counting of white blood cells (WBCs) in bone marrow using artificial intelligence
(AI)-based models, such as convolutional neural network (CNN) and its various variants, can …
(AI)-based models, such as convolutional neural network (CNN) and its various variants, can …
Segmentation of cardiac tissues and organs for CCTA images based on a deep learning model
Accurate segmentation of cardiac tissues and organs based on cardiac computerized
tomography angiography (CCTA) images has played an important role in biophysical …
tomography angiography (CCTA) images has played an important role in biophysical …
Quantification of Fundus Autofluorescence Features in a Molecularly Characterized Cohort of More Than 3500 Inherited Retinal Disease Patients from the United …
W Woof, TAC de Guimarães, S Al-Khuzaei… - medRxiv, 2024 - medrxiv.org
Purpose To quantify relevant fundus autofluorescence (FAF) image features cross-
sectionally and longitudinally in a large cohort of inherited retinal diseases (IRDs) patients …
sectionally and longitudinally in a large cohort of inherited retinal diseases (IRDs) patients …
A systematic study of the performance of machine learning models on analyzing the association between semen quality and environmental pollutants
Human exposure to Phthalates, a family of chemicals primarily used to enhance the
flexibility and durability of plastics, could lead to a decline in semen quality. Extensive …
flexibility and durability of plastics, could lead to a decline in semen quality. Extensive …