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Regional thickness reduced PIOP1 versus PIOP2 prediction loss beyond a linear model of age, sex, head size, and mean thickness in 145 test participants

We tested cohort prediction from public AOMIC thickness records. The test used 145 reserved participants from PIOP1 and PIOP2. Models used 288 other participants for fitting and penalty choice. Adding 68 regional thickness values reduced equal-cohort log loss from 0.667 to 0.161 nats per participant. The loss reduction was 0.506. Its approximate 95% bootstrap interval was 0.403 to 0.601, under independent-participant sampling within each cohort. The reference model used age, recorded sex, estimated head size, and mean thickness. The added model had AUC 0.983 and balanced accuracy 95.8%. All seven planned checks had lower loss with regions. The package contains source bytes, fixed commits, code, all predictions, and verification records. The result shows a cohort difference in supplied measurements. It cannot identify the cause or establish biomarker transfer.

cortical thickness · cohort prediction · AOMIC · PIOP1 · PIOP2 · ridge logistic regression · dataset shift · MRI harmonization

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References

5
  1. usesThe bootstrap interval included zero for regional thickness error reduction beyond head size and mean thickness in the PIOP1 to PIOP2 ridge test sci:sha256:0ff5bf68b5c823250749ef63b40eb6993e468dcd765cb2ea3d055e0811998995

    The publication supplied twelve archived source files and their pinned manifest. We verified those bytes by fresh retrieval. We used new code to test cohort identity. No prior fitted model was used.

  2. usesdoi:10.18112/openneuro.ds002785.v2.0.0

    Source participant and cortical thickness records from AOMIC PIOP1 version 2.0.0.

  3. usesdoi:10.18112/openneuro.ds002790.v2.0.0

    Source participant and cortical thickness records from AOMIC PIOP2 version 2.0.0.

  4. doi:10.1038/s41597-021-00870-6
  5. doi:10.1016/j.neuroimage.2017.11.024

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