Enhancing early detection of cognitive decline in the elderly: a comparative study utilizing large language models in clinical notes
X Du, J Novoa-Laurentiev, JM Plasek, YW Chuang… - …, 2024 - thelancet.com
Summary Background Large language models (LLMs) have shown promising performance
in various healthcare domains, but their effectiveness in identifying specific clinical …
in various healthcare domains, but their effectiveness in identifying specific clinical …
Assessing the Significance of Longitudinal Data in Alzheimer's Disease Forecasting
BK Karaman, MR Sabuncu - International Conference on AI in Healthcare, 2024 - Springer
In this study, we employ a transformer encoder model to characterize the significance of
longitudinal patient data for forecasting the progression of Alzheimer's Disease (AD). Our …
longitudinal patient data for forecasting the progression of Alzheimer's Disease (AD). Our …
MRI-based mild cognitive impairment and Alzheimer's disease classification using an algorithm of combination of variational autoencoder and other machine learning …
Background Correctly diagnosing mild cognitive impairment (MCI) and Alzheimer's disease
(AD) is important for patient selection in drug discovery. Research outcomes on stage …
(AD) is important for patient selection in drug discovery. Research outcomes on stage …
Enhancing Early Detection of Cognitive Decline in the Elderly through Ensemble of NLP Techniques: A Comparative Study Utilizing Large Language Models in …
X Du, J Novoa-Laurentiev, JM Plasek… - Medrxiv: the Preprint …, 2024 - europepmc.org
Background Early detection of cognitive decline in elderly individuals facilitates clinical trial
enrollment and timely medical interventions. This study aims to apply, evaluate, and …
enrollment and timely medical interventions. This study aims to apply, evaluate, and …