Deep learning for Alzheimer's disease diagnosis: A survey
Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
Application of artificial intelligence technology in oncology: Towards the establishment of precision medicine
Simple Summary Artificial intelligence (AI) technology has been advancing rapidly in recent
years and is being implemented in society. The medical field is no exception, and the clinical …
years and is being implemented in society. The medical field is no exception, and the clinical …
A survey on the interpretability of deep learning in medical diagnosis
Deep learning has demonstrated remarkable performance in the medical domain, with
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
accuracy that rivals or even exceeds that of human experts. However, it has a significant …
Learning models for suicide prediction from social media posts
We propose a deep learning architecture and test three other machine learning models to
automatically detect individuals that will attempt suicide within (1) 30 days and (2) six …
automatically detect individuals that will attempt suicide within (1) 30 days and (2) six …
Explanation-driven HCI model to examine the mini-mental state for Alzheimer's disease
Directing research on Alzheimer's disease toward only early prediction and accuracy cannot
be considered a feasible approach toward tackling a ubiquitous degenerative disease …
be considered a feasible approach toward tackling a ubiquitous degenerative disease …
An explainable machine learning approach for Alzheimer's disease classification
The early diagnosis of Alzheimer's disease (AD) presents a significant challenge due to the
subtle biomarker changes often overlooked. Machine learning (ML) models offer a …
subtle biomarker changes often overlooked. Machine learning (ML) models offer a …
[PDF][PDF] Modular Multi-Modal Attention Network for Alzheimer's Disease Detection Using Patient Audio and Language Data.
In this work, we propose a modular multi-modal architecture to automatically detect
Alzheimer's disease using the dataset provided in the ADReSSo challenge. Both acoustic …
Alzheimer's disease using the dataset provided in the ADReSSo challenge. Both acoustic …
Single and combined neuroimaging techniques for Alzheimer's disease detection
Alzheimer's disease (AD) consists of the gradual process of decreasing volume and quality
of neuron connection in the brain, which consists of gradual synaptic integrity and loss of …
of neuron connection in the brain, which consists of gradual synaptic integrity and loss of …
Multi-channel, convolutional attention based neural model for automated diagnostic coding of unstructured patient discharge summaries
Effective coding of patient records in hospitals is an essential requirement for epidemiology,
billing, and managing insurance claims. The prevalent practice of manual coding, carried …
billing, and managing insurance claims. The prevalent practice of manual coding, carried …
Decoding loneliness: Can explainable AI help in understanding language differences in lonely older adults?
Study objectives Loneliness impacts the health of many older adults, yet effective and
targeted interventions are lacking. Compared to surveys, speech data can capture the …
targeted interventions are lacking. Compared to surveys, speech data can capture the …