feat: implement backend image classification with TensorFlow.js model

- Extend shared types for image classification, including PredictionProbability, UploaderMetadata, and ImageClassificationRecord.
- Create image_classifications table in the database with necessary fields and foreign key constraints.
- Implement disease mappers to convert database rows to shared disease records.
- Develop uploader client to handle image uploads to external service.
- Create image model service to load and classify images using TensorFlow.js.
- Add API routes for image classification, including GET for history and POST for new classifications.
- Implement frontend components for image classification form and display results.
- Update dashboard to integrate image classification functionality and display results.
- Document implementation plan for backend image classification.

apps/api/drizzle/meta/_journal.json

@@ -8,6 +8,13 @@
       "when": 1779458573080,
       "tag": "0000_harsh_arachne",
       "breakpoints": true
+    },
+    {
+      "idx": 1,
+      "version": "7",
+      "when": 1779461286348,
+      "tag": "0001_cute_lyja",
+      "breakpoints": true
     }
   ]
 }