[HTML][HTML] A Comprehensive Review of Explainable AI for Disease Diagnosis
AA Biswas - Array, 2024 - Elsevier
Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare
sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited …
sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited …
Time-series anonymization of tabular health data using generative adversarial network
Data anonymization has been used as a fundamental tool in various domains, eg
healthcare, to alter personal data such that individuals can no longer be identified directly or …
healthcare, to alter personal data such that individuals can no longer be identified directly or …
Transfer Learning for Alzheimer's Disease Diagnosis from MRI Slices: A Comparative Study of Deep Learning Models
GI Stoleru, A Iftene - Procedia Computer Science, 2023 - Elsevier
The early detection of Alzheimer's disease is a significant research priority in the field, as it
enables timely medical intervention and treatment that may potentially slow down the …
enables timely medical intervention and treatment that may potentially slow down the …
A Novel Artificial Intelligence (AI) Method to Classify and Predict the Progression of Alzheimers Disease
Purpose: The objective of this study was to develop a novel AI-ensembled network based on
the most important features and affected brain regions to accurately classify and exhibit the …
the most important features and affected brain regions to accurately classify and exhibit the …
Enhancement and Evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D Knowledge Distillation
H Yoon, DY Kang, S Kim - 2024 - researchsquare.com
The application of deep learning techniques for the analysis of neuroimaging has been
increasing recently. The 3D Convolutional Neural Network (CNN) technology, which is …
increasing recently. The 3D Convolutional Neural Network (CNN) technology, which is …