Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data
Despite the remarkable advances in cancer diagnosis, treatment, and management over the
past decade, malignant tumors remain a major public health problem. Further progress in …
past decade, malignant tumors remain a major public health problem. Further progress in …
Artificial intelligence–based image analysis in clinical testing: lessons from cervical cancer screening
Novel screening and diagnostic tests based on artificial intelligence (AI) image recognition
algorithms are proliferating. Some initial reports claim outstanding accuracy followed by …
algorithms are proliferating. Some initial reports claim outstanding accuracy followed by …
Design of the HPV-automated visual evaluation (PAVE) study: Validating a novel cervical screening strategy
S de Sanjosé, RB Perkins, N Campos, F Inturrisi… - Elife, 2024 - elifesciences.org
Background: The HPV-automated visual evaluation (PAVE) Study is an extensive,
multinational initiative designed to advance cervical cancer prevention in resource …
multinational initiative designed to advance cervical cancer prevention in resource …
Machine learning models for diagnosis and prognosis of Parkinson's disease using brain imaging: general overview, main challenges, and future directions
B Garcia Santa Cruz, A Husch, F Hertel - Frontiers in Aging …, 2023 - frontiersin.org
Parkinson's disease (PD) is a progressive and complex neurodegenerative disorder
associated with age that affects motor and cognitive functions. As there is currently no cure …
associated with age that affects motor and cognitive functions. As there is currently no cure …
FirePred: A hybrid multi-temporal convolutional neural network model for wildfire spread prediction
Wildfires represent a significant natural disaster with the potential to inflict widespread
damage on both ecosystems and property. In recent years, there has been a growing …
damage on both ecosystems and property. In recent years, there has been a growing …
Uncertainty-aware Health Diagnostics via Class-balanced Evidential Deep Learning
Uncertainty quantification is critical for ensuring the safety of deep learning-enabled health
diagnostics, as it helps the model account for unknown factors and reduces the risk of …
diagnostics, as it helps the model account for unknown factors and reduces the risk of …
[HTML][HTML] Capturing and interpreting wildfire spread dynamics: attention-based spatiotemporal models using ConvLSTM networks
Predicting the trajectory of geographical events, such as wildfire spread, presents a
formidable task due to the dynamic associations among influential biophysical factors. Geo …
formidable task due to the dynamic associations among influential biophysical factors. Geo …
A novel deep learning framework for rolling bearing fault diagnosis enhancement using VAE-augmented CNN model
Y Wang, D Li, L Li, R Sun, S Wang - Heliyon, 2024 - cell.com
In the context of burgeoning industrial advancement, there is an increasing trend towards
the integration of intelligence and precision in mechanical equipment. Central to the …
the integration of intelligence and precision in mechanical equipment. Central to the …
Multinational external validation of autonomous retinopathy of prematurity screening
Importance Retinopathy of prematurity (ROP) is a leading cause of blindness in children,
with significant disparities in outcomes between high-income and low-income countries, due …
with significant disparities in outcomes between high-income and low-income countries, due …
Assessing generalizability of an AI-based visual test for cervical cancer screening
A number of challenges hinder artificial intelligence (AI) models from effective clinical
translation. Foremost among these challenges is the lack of generalizability, which is …
translation. Foremost among these challenges is the lack of generalizability, which is …