A magnetic resonance diffusion tensor imaging analysis of the hippocampus in patients with mild cognitive impairment
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
Objective To investigate the difference of average diffusion coefficient(ADC) and fractional anisotropy(FA) in the hippocampus(HP) of aged groups that have mild cognitive impairment(MCI) and that have normal cognition,and to evaluate the applicability of magnetic resonance diffusion tensor imaging(MR-DTI) in MCI diagnosis.Methods We selected a total of 18 MCI patients(MCI Group) and 18 individuals with normal cognition(NC Group),the two groups being matched by gender,age and education.A comparison was done for the two groups in ADC and FA in the HP.A possible correlation between the ADC and FA values of the MCI patients and their Mini-Mental State Examination(MMSE),Montreal Cognitive Assessment(MoCA),and Activities of Daily Living(ADL) scores was examined.Results Compared with the NC Group,the MCI Group exhibited significantly high ADC for the left HP and the total bilateral HP(P0.01),whereas the two groups were not significantly different in the right HP(P0.05).With FA,the two groups were not significantly different in the left,right and total bilateral HP(P0.05).The MCI Group had lower MMSE and MoCA scores,but higher ADL scores than the NC Group(P0.01).In addition,MMSE showed a negative correlation with ADC of the left HP and total bilateral HP(P0.01),but had no significant correlation with either FA or ADC of the right HP(P0.05).Furthermore,MoCA and ADL did not have significant correlation with either ADC or FA(P0.05).Conclusion MR-DTI is a helpful tool in MCI diagnosis.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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