💻Technical Architecture

Dr.Blake’s technical stack integrates deep learning with decentralized protocols across five major components:

1. AI Model Layer (Diagnostic Engine)

• Combines deep convolutional neural networks (CNNs) and Transformer architectures, trained on varied medical images (e.g., hybrid ResNet + ViT)

• Multi-task learning to simultaneously output classification (e.g., anomaly type) and localization (e.g., heatmaps, high-risk zones)

• Retrained quarterly via DAO-approved datasets to adapt to regional and global pathological variations

2. Inference & Deployment Framework

• Uses ONNX model format to support WebAssembly, edge devices, and mobile environments

• Enables lightweight deployments for local preprocessing to protect privacy

• Cloud nodes serve as high-accuracy validators, cross-checking results from low-power devices

3. Data Storage & Access Control

• Medical images and reports stored on IPFS with hash-bound identity anchoring

• Supports zkStorage for encrypted data, accessible only by users or authorized parties

• Report summaries committed to L2 chains (e.g., Arbitrum) for immutability and auditability

4. API & Developer Integration

• RESTful and GraphQL APIs for seamless access to diagnostic services

• SDKs available for integration with HIS, PACS, telehealth platforms, and Web3 wallets

• Full documentation and sample calls support cross-chain verifications

5. Security & Compliance

• TLS + AES-256 encryption for all transmissions; compliant with HIPAA and global standards

• Full data access and deletion rights for users; anonymous report participation without KYC

• DAO-led audit committee reviews model misdiagnoses and ensures accountability