Development of a telemedicine protocol for the diagnosis of Alzheimer's disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We developed a telemedicine protocol for diagnosis of Alzheimer's Disease (AD). Assessments by video-conferencing (remote) were compared with face to face (direct) assessments. Eight physicians performed direct assessments and two physicians conducted remote assessments. There was alternate allocation of direct or remote initial assessment. The participants were 20 subjects over 65 years living in a rural area and referred by general practitioners (GPs) because of cognitive impairment. Each assessment included a Standardised Mini Mental State Examination, Geriatric Depression Scale, Katz assessment of Activities of Daily Living, Instrumental ADL assessment, and the Informant Questionnaire for Cognitive Decline in the Elderly. Laboratory results and radiological imaging were available from referring GPs. There was good agreement for diagnosing Alzheimer's disease between telemedicine and direct assessment, kappa = 0.8 (P<0.0001). However, because of the small sample size, the presence of systematic bias could not be completely excluded. We conclude that it is possible to diagnose AD at a distance using telemedicine, but this requires validation with a larger study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it