Tooling
Why 3D Medical Imaging Models Plateau at 55% Accuracy
A machine learning practitioner working with the ADNI neuroimaging dataset reports accuracy stuck at 55% when training 3D models on .npy files. The plateau reveals common data and architecture pitfalls in medical imaging
1 min read
Sourcer/machinelearning
A machine learning practitioner working with the ADNI neuroimaging dataset reports accuracy stuck at 55% when training 3D models on .npy files. The goal is 90% accuracy, but the model refuses to improve beyond the midpoint.
This is a textbook case of architectural mismatch, not a data problem. When...
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Method & sources
- Source type
- Primary publication (lab/vendor blog) — our analysis + implication
- Source link
- r/machinelearning
- Published
- UTC
- Byline
- By the gotcontext.ai team (editorial standards)
- Correction?
- corrections@gotcontext.ai