Large Language Model for Understanding and Monitoring Elderly Neurocognition
NCT07347431 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 60
Last updated 2026-04-21
Summary
Dementia affects millions of people worldwide, and early diagnosis is essential for getting the right care and support. Doctors rely on collateral histories (accounts from family members or caregivers) to understand changes in a person's memory and thinking. However, these histories can be incomplete, unstructured, or difficult to obtain, making diagnosis more challenging.
This study will test LUMEN (Large Language Model for Understanding and Monitoring Elderly Neurocognition), an AI-powered conversation tool designed to help caregivers describe their loved one's symptoms more effectively. By asking structured questions and guiding the conversation, LUMEN can create clear, well-organised reports for memory clinic doctors. This could make assessments quicker, more accurate, and less stressful for families.
We will test LUMEN in real-world clinics by asking caregivers and doctors to use it and provide feedback. We want to understand how easy it is to use, whether it could improve the quality of information shared, and how it fits into existing NHS memory clinic processes. We will also run co-production workshops with community groups to ensure the tool is accessible to people from diverse cultural and language backgrounds.
This research is exciting because it explores how artificial intelligence can improve dementia care. If successful, LUMEN could enhance the diagnostic process, reduce carer burden, and help more people access dementia support sooner. In the future, this tool could be used nationwide in memory clinics, improving care for thousands of families.
Conditions
Interventions
- OTHER
-
LUMEN prototype software interaction
This is a prototype software which seeks to gather collateral information relevant to a dementia clinical assessment.
Sponsors & Collaborators
-
Newcastle University
collaborator OTHER -
Northumbria Healthcare NHS Foundation Trust
lead OTHER
Principal Investigators
-
Judith R Harrison, MBChB PhD · Northumbria Healthcare NHS Foundation Trust
Eligibility
- Min Age
- 65 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2026-03-19
- Primary Completion
- 2026-12-31
- Completion
- 2026-12-31
Countries
- United Kingdom
Study Locations
More Related Trials
-
Using Large Language Models Such As GPT-4 to Assess Guideline Adherence in Patients With Chronic Obstructive Pulmonary Disease
NCT06410547 ·Status: COMPLETED ·Phase: NA
-
The Diagnostic and Triage Capacity of Laypeople-large Language Model Collaboration in China
NCT07250516 ·Status: COMPLETED ·Phase: NA
-
Artificial Intelligence in Mental Illness Diagnosis and Treatment
NCT04515173 ·Status: UNKNOWN ·Phase: NA
-
The Effects of a Large Language Model on Clinical Questioning Skills
NCT06229379 ·Status: COMPLETED ·Phase: NA
-
Multi-Disciplinary Treatment on the Anthropomorphism of Large Language Models
NCT06627985 ·Status: NOT_YET_RECRUITING
-
Enhancing Medical Researchers' Self-learning With an Intelligent Language Model
NCT06015178 ·Status: UNKNOWN ·Phase: NA
-
Artificial Intelligence - SARS-CoV-2 (COVID-19) Risk Evaluation
NCT04834934 ·Status: COMPLETED
-
Evaluation of AI-Generated Clinical Advice by Physicians
NCT06980467 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Atrial Fibrillation Recurrence Prediction
NCT06977516 ·Status: COMPLETED
-
Evaluating the Real World Performance of an AI Based Lung Nodule Detection Tool
NCT06597968 ·Status: RECRUITING
-
AI Ethical Assessment in Scientific Resreach
NCT07340905 ·Status: NOT_YET_RECRUITING
-
A Platform for Multidisciplinary Medical Artificial Intelligence Development
NCT04890847 ·Status: UNKNOWN
-
AI-Driven Consent Simplification Study
NCT07303517 ·Status: RECRUITING
-
Feasibility Study for Improving the Relevance of Diagnostic Proposals for an Artificial Intelligence Software in the Elderly Population.
NCT04242043 ·Status: COMPLETED
-
Large Language Model-Generated Messages to Improve Guideline-Directed Medical Therapy in Heart Failure
NCT07337577 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
Large Language Models To Improve the Quality of Care of Cardiology Patients
NCT06935253 ·Status: RECRUITING ·Phase: NA
-
AI-LLM Communication Aid in Prostate Cancer Care (AI-CAP)
NCT07082049 ·Status: ENROLLING_BY_INVITATION ·Phase: NA
-
Evaluating AI-Generated Plain Language Summaries on Patient Comprehension of Ophthalmology Notes Among English-Speaking Patients
NCT06859216 ·Status: RECRUITING ·Phase: NA
-
Development of an AI-based Emergency Imaging Multi-Disease Rapid Joint Screening System
NCT05974163 ·Status: UNKNOWN
-
A Randomized Controlled Trial of Robotic Support for Enhanced Later Life (RoSELL)
NCT07102017 ·Status: ACTIVE_NOT_RECRUITING ·Phase: NA
-
Physician Reasoning on Diagnostic Cases With Large Language Models
NCT06157944 ·Status: COMPLETED ·Phase: NA
-
Testing an AI Large Language Model Tool for Cognitive Debiasing in Musculoskeletal Care
NCT07022769 ·Status: NOT_YET_RECRUITING ·Phase: NA
-
The Application of Large Language Model in Emergency Chest Pain Triage
NCT06493175 ·Status: RECRUITING ·Phase: NA
-
Clinical Application of Automated Interpretation System for Chest X-Ray Images Based on Multimodal Large Models
NCT07117266 ·Status: COMPLETED ·Phase: NA
-
AI-Assisted Medical Decision-Making
NCT06846229 ·Status: RECRUITING