---
license: apache-2.0
language:
- en
pretty_name: Dental Clinical Assistant 20B
base_model:
- openai/gpt-oss-20b
library_name: transformers
pipeline_tag: text-generation
tags:
- structured treatment planning
- structured output
- supervised fine tuning
- sft
- dental
- dentistry
- dental ai
- dental clinical assistant
- clinical decision support
- diagnosis
- treatment planning
- evidence based
- dental emergencies
- antibiotic stewardship
- guideline adherence
- dental guidelines
- endodontics
- periodontics
- oral surgery
- prosthodontics
- orthodontics
- pediatric dentistry
- dental radiology
- differential diagnosis
- risk assessment
- triage
- case reasoning
- chairside assistant
- point of care
- medical
- healthcare
- clinical reasoning
- synthetic data
- hipaa compliant
datasets:
- Wildstash/dental-2.5k-instruct
model-index:
- name: Wildstash/dental-clinical-assistant-20b
  results:
  - task:
      type: text-generation
      name: Dental clinical QA (internal heuristic)
    dataset:
      name: Wildstash/dental-2.5k-instruct
      type: Wildstash/dental-2.5k-instruct
      split: test
    metrics:
    - type: clinical_guideline_adherence
      value: 0.90
    - type: reasoning_transparency
      value: 0.92
widget:
- text: "Evaluate dental emergency: 45M, severe tooth pain, facial swelling, fever 101°F. Give differential, immediate management, antibiotics, follow up."
  parameters: {max_new_tokens: 400, temperature: 0.7}
- text: "Periodontics: 52F with generalized 6–8 mm pockets and bleeding. Stage and grade, risk, and 90‑day treatment plan."
  parameters: {max_new_tokens: 350, temperature: 0.7}
- text: "Endodontics: 33M, #19 lingering cold sensitivity, severe biting pain. Diagnose and outline RCT vs extraction decision."
  parameters: {max_new_tokens: 350, temperature: 0.7}
- text: "Oral surgery: Impacted mandibular third molar with pericoronitis. Indications, risks, and peri‑op antibiotics."
  parameters: {max_new_tokens: 320, temperature: 0.7}
---

# Dental Clinical Assistant 20B

Chat assistant for structured treatment planning and clinical decision support (SFT)


Open source dental clinical assistant for diagnosis, treatment planning, and point‑of‑care decision support.

## Quickstart (LoRA adapter)
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
import torch

base = "openai/gpt-oss-20b"
adapter = "Wildstash/dental-clinical-assistant-20b"

tok = AutoTokenizer.from_pretrained(base, trust_remote_code=True)
base_model = AutoModelForCausalLM.from_pretrained(base, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True)
model = PeftModel.from_pretrained(base_model, adapter)
```


## 🏆 Awards
- Winner: Most Useful Fine‑Tune (OpenAI Open Model Hackathon) — see Devpost: https://devpost.com/software/dental-assessment-gpt

## Structured output
- Differential diagnosis
- Management plan
- Antibiotics and dosing (if indicated)
- Follow-up protocol


## Quick guide (read this)
- What it is: Chat assistant for structured treatment planning and clinical decision support (SFT).
- What it covers: endodontics, periodontics, oral surgery, prosthodontics, ortho, pediatrics.
- Why trust it: trained on 2,494 expert‑validated synthetic cases; guideline‑aligned.
- How to use: provide patient context (age, vitals, symptoms, exam); ask for differential, management, abx, follow‑up.
- Safety: HIPAA‑friendly (no real patient data); outputs assist, not replace, clinical judgment.

### Dataset statistics
- 2,494 cases; multi‑specialty coverage; structured JSON (presentation → assessment → plan).
- Source: `Wildstash/dental-2.5k-instruct`.

### Key features
- Comprehensive dental coverage; evidence‑based plans; guideline adherence; step‑wise reasoning.

### Training details
- Method: LoRA (PEFT), 4‑bit; base: 20B decoder.
- Optimizations: grad checkpointing; mixed precision; multi‑GPU.

### Expert validation
- Practicing dentists graded sample cases; refined to improve plausibility and completeness.