AI stack

DXAI leverages a specialized AI stack that is purpose-built for medical diagnostics, combining advanced architectures, domain-specific training, and scalable deployment. Unlike general-purpose large language models (LLMs), our platform focuses on accuracy, interpretability, and efficiency in healthcare-specific applications.

Key Components of the DXAI AI Stack:

1. Model Architectures:

   • Vision Transformers (ViTs) and CNNs for medical image analysis.

   • Fine-tuned LLMs (e.g., Llava-Med, Mistral) for text-based diagnostics and reasoning.

2. Domain-Specific Training:

   • Trained on curated datasets such as SinoCT (CT scans), ISIC (dermatological images), and MURA (radiographs).

   • Specialized tuning ensures higher performance in sensitivity, specificity, and precision compared to generalized models.

3. Real-Time Capabilities:

   • Scalable architecture for processing thousands of cases daily.

   • Decentralized integration using $DXAI tokens for seamless access.

Advantages of DXAI Over Commercial LLMs:

• Precision: Domain-specific models outperform general LLMs in medical diagnostics by up to 20%.

• Efficiency: Optimized for medical tasks, reducing computational overhead.

• Interpretable Outputs: Provides heatmaps, overlays, and context-aware reasoning for clinicians.

• Decentralization: Blockchain-backed transparency and incentivization.

In a nutshell, considering commercial LLMs, this is the difference between our implementations and commercial LLMs: