The Algorithm of Grief: From Loss to Legacy
summary
Proposes a hybrid ML architecture combining CNN for skin images with RNN for patient time-series to detect scleroderma earlier, targeting high sensitivity and specificity. Cites disease rarity at ≈3 per 100,000 as the key data scarcity challenge. Claims the model could find subtle texture, color and vascular patterns plus longitudinal blood-test/symptom trends invisible to clinicians. Status: architecture and training plan sketched, no dataset assembled and no code or validation yet; calls for collaborators and data.
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chapters (5)
- 0:00Introduction and personal story
- 7:57Understanding scleroderma
- 13:23Machine learning for early detection
- 16:36Hybrid model approach
- 24:32Call for collaboration and Q&A
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