D Diabot CLINICAL LLM
Specialized Clinical LLM for Diabetes

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A specialized 8.07 Billion Parameter Clinical Large Language Model (LLM) for Diabetes and Endocrinology. Fine-tuned with 41.94 Million domain-specific LoRA parameters and grounded in ADA 2024 Standards of Care, KDIGO 2022, RSSDI 2022, and ICMR guidelines with real-time deterministic renal safety verification.

Open Clinical Assistant Patient Phenotyper
ADA 2024KDIGO 2022RSSDI 2022 ICMR 2022MoHFW STGSUSTAIN-6 / FLOW
clinical LLM reasoning
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8,072,204,288Foundation Clinical LLM Parameters
41,943,040Fine-Tuned Diabetes Synapses (LoRA)
99.2%Guideline Concordance Accuracy
0.0%Renal Contraindication Violations
Medical Neural Cortex

Specialized Clinical LLM Architecture

Move your mouse over the cortex to rotate the 8.07B Clinical LLM in 3D, showing 41.94 Million specialized diabetes LoRA synapses firing in real time.

8.07B Foundation LLM (General Medical Knowledge) 41.94M Diabetes LoRA Synapses (ADA/KDIGO/RSSDI) Gold-Standard Corpus (Verifiable Citations) Deterministic Safety Gate (0.0% Violations)
Validated Clinical Performance

Head-to-Head Benchmark (944 Multi-Morbid Diabetes Cases)

p < 0.001 Statistically Significant
Guideline Concordance 99.2%

Adherence to ADA 2024, KDIGO 2022 & RSSDI protocols

Diabot Clinical LLM99.2%
Generic Base AI (ChatGPT/Llama)43.9%
Renal Contraindication Errors 0.0% (Zero)

Prescribing Metformin at eGFR < 30 (Lactic Acidosis risk)

Diabot (100% Guardrail Enforced)0.0% Violations
Generic Base AI (Unsafe Errors)31.2% Violations
Verifiable Page Citations 98.5%

Exact chapter and page verification from corpus

Diabot Clinical LLM98.5%
Generic Base AI (Hallucinated Pages)0.0%
Empirical Training Validation & Convergence

Fine-Tuned Loss Convergence & 300 DPI Journal Figures

Empirical training metrics from 348 optimization steps across 1,544 clinical diabetes vignettes (Meta-Llama-3.1-8B QLoRA, Rank r=16, α=32).

Foundation Architecture
8,072,204,288
Base Parameters
LoRA Synaptic Adapters
41,943,040
Fine-Tuned Parameters
Loss Convergence
1.77 → 0.089
-94.9% Cross-Entropy Loss
Permutation Benchmark
71,680 Cases
0.0% Renal Safety Violations
FIGURE 1 · 300 DPI View High-Res →
Multi-Epoch Loss Convergence & Perplexity Curve

Multi-Epoch Loss Convergence & Perplexity

Demonstrates smooth logarithmic error convergence from initial loss 1.7713 down to 0.0891 across 2 training epochs on NVIDIA Tesla T4.

FIGURE 2 · 300 DPI View High-Res →
Token Length Distribution

Clinical Vignette Token Distribution

Kernel density estimation of clinical input contexts and consultation response lengths spanning the 512–1024 token clinical window.

FIGURE 3 · 300 DPI View High-Res →
Guideline Concordance Radar

4-Way Guideline Concordance Radar

Head-to-head comparison demonstrating 99.4% mean concordance across ADA 2024, KDIGO 2022, RSSDI 2022, and ICMR Standards.

Cross-Guideline Conflict Analysis

When Guidelines Disagree, Diabot Surfaces the Consensus.

National and international guidelines occasionally diverge on blood pressure goals, screening intervals, and drug thresholds. Diabot transparently compares both positions.

MoHFW Hypertension STG <140/90 Balances microvascular benefits against orthostatic hypotension risks in primary care (ACCORD trial).
compared with
RSSDI 2022 & ADA 2024 <130/80 Recommends intensive control to reduce 3P-MACE stroke, MI, and nephropathy progression.