Artificial intelligence-based methods for fusion of electronic health records and imaging data

F Mohsen, H Ali, N El Hajj, Z Shah - Scientific Reports, 2022 - nature.com
Healthcare data are inherently multimodal, including electronic health records (EHR),
medical images, and multi-omics data. Combining these multimodal data sources …

Unveiling new strategies facilitating the implementation of artificial intelligence in neuroimaging for the early detection of Alzheimer's disease

MO Etekochay, AR Amaravadhi… - Journal of …, 2024 - content.iospress.com
Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The
past few decades have witnessed significant strides in comprehending the underlying …

Multimodal ensemble model for Alzheimer's disease conversion prediction from Early Mild Cognitive Impairment subjects

M Velazquez, Y Lee - Computers in biology and medicine, 2022 - Elsevier
Alzheimer's Disease (AD) is the most common type of dementia. Predicting the conversion to
Alzheimer's from the mild cognitive impairment (MCI) stage is a complex problem that has …

Screening strategies and dynamic risk prediction models for Alzheimer's disease

X Ge, K Cui, Y Qin, D Chen, H Han, H Yu - Journal of psychiatric research, 2023 - Elsevier
Background Characterizing the progression from Mild cognitive impairment (MCI) to
Alzheimer's disease (AD) is essential for early AD prevention and targeted intervention. Our …

Apathy as a predictor of conversion from mild cognitive impairment to Alzheimer's disease: a Texas Alzheimer's Research and Care Consortium (TARCC) cohort …

H Salem, R Suchting, MM Gonzales… - Journal of …, 2023 - content.iospress.com
Background: Apathy is among the neuropsychiatric symptoms frequently observed in people
with cognitive impairment. It has been postulated to be a potential predictor of conversion …

A Deep Longitudinal Model for Mild Cognitive Impairment to Alzheimer's Disease Conversion Prediction in Low‐Income Countries

A Akhtar, S Minhas, N Sabahat… - … Intelligence and Soft …, 2022 - Wiley Online Library
Alzheimer's disease (AD) is a progressive and fatal disease, due to the nonavailability of any
permanent cure. Some treatments are under experimentation that can slow down and …

A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease

MW Lee, HW Kim, YS Choe, HS Yang, J Lee, H Lee… - Scientific Reports, 2024 - nature.com
Alzheimer's disease (AD) accounts for 60–70% of the population with dementia. Mild
cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between …

Intelligent prediction of Alzheimer's disease via improved multifeature squeeze-and-excitation-dilated residual network

Z Yuan, X Li, Z Hao, Z Tang, X Yao, T Wu - Scientific Reports, 2024 - nature.com
This study aimed to address the issue of larger prediction errors existing in intelligent
predictive tasks related to Alzheimer's disease (AD). A cohort of 487 enrolled participants …

Predicting Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using K-Means Clustering on MRI Data

M Bellezza, A di Palma, A Frosini - Information, 2024 - mdpi.com
Alzheimer's disease (AD) is a neurodegenerative disorder that leads to the loss of cognitive
functions due to the deterioration of brain tissue. Current diagnostic methods are often …

Overview of Artificial Intelligence Methods for Alzheimer's Disease Prediction and Progression

C Comito, C Pizzuti, M Sammarra - 2023 17th International …, 2023 - ieeexplore.ieee.org
Years of dedicated experimental and clinical investigations have shed light on numerous
aspects of Alzheimer's disease (AD) pathogenesis. However, the are still many facets and …