> ## Documentation Index
> Fetch the complete documentation index at: https://assemblyai.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Medical Mode

export const ModelBadges = ({models}) => {
  return <div className="flex flex-wrap gap-2 -mt-3 mb-3 not-prose">
      {models.map(model => <span key={model} className="inline-flex items-center rounded-full bg-green-500/15 px-2.5 py-0.5 text-xs font-mono text-green-700 dark:text-green-400 ring-1 ring-inset ring-green-500/30">
          {model}
        </span>)}
    </div>;
};

export const AudioPlayer = ({src, type = "audio/mpeg", fallbackText = "Your browser does not support the audio element."}) => {
  return <audio controls style={{
    width: "100%"
  }}>
      <source src={src} type={type} />
      {fallbackText} <a href={src}>Download the audio</a>.
    </audio>;
};

<ModelBadges models={["universal-3-5-pro", "universal-streaming-english", "universal-streaming-multilingual"]} />

Medical Mode is an add-on that enhances streaming transcription accuracy for medical terminology — including medication names, procedures, conditions, and dosages. It is optimized for medical entity recognition to correct terms that other models frequently get wrong.

Medical Mode can be used with all of our Real-time STT models.

Enable Medical Mode by setting the `domain` connection parameter to `"medical-v1"`. No other changes to your existing pipeline are required.

## Quickstart

Set `domain` to `"medical-v1"` as a connection parameter when you open the WebSocket.

<Tabs>
  <Tab language="python" title="Python" default>
    ```python theme={null}
    CONNECTION_PARAMS = {
        "sample_rate": 16000,
        "speech_model": "universal-3-5-pro",
        "domain": "medical-v1",
    }
    ```
  </Tab>

  <Tab language="python-sdk" title="Python SDK">
    ```python theme={null}
    client.connect(
        StreamingParameters(
            sample_rate=16000,
            speech_model="universal-3-5-pro",
            domain="medical-v1",
        )
    )
    ```
  </Tab>

  <Tab language="javascript" title="Javascript">
    ```javascript theme={null}
    const CONNECTION_PARAMS = {
      sample_rate: 16000,
      speech_model: "universal-3-5-pro",
      domain: "medical-v1",
    };
    ```
  </Tab>

  <Tab language="javascript-sdk" title="JavaScript SDK">
    ```javascript theme={null}
    const transcriber = client.streaming.transcriber({
      sampleRate: 16_000,
      speechModel: "universal-3-5-pro",
      domain: "medical-v1",
    });
    ```
  </Tab>
</Tabs>

<AudioPlayer src="https://assemblyaiassets.com/56e2be1c-lispro.mp3" />

### Example output

Without Medical Mode:

```plain theme={null}
I have here insulin to be used for both prandial mealtime and sliding scale is
insulin lisprohumalog subcutaneously.
```

With Medical Mode, lisprohumalog is updated to Lispro (Humalog) - following the standard medical convention of writing the generic name first, with the brand name in parentheses.

```plain theme={null}
I have here insulin to be used for both prandial mealtime and sliding scale is
insulin Lispro (Humalog) subcutaneously.
```

## Use cases

Medical Mode is designed for healthcare AI applications where accurate medical terminology is critical:

* **Ambient clinical documentation** — Capture medication names, dosages, and clinical terms correctly during live patient encounters.
* **Real-time medical scribes** — Deliver accurate transcripts to clinicians during or immediately after a consult.
* **Front-office voice agents** — Handle drug names, provider names, and clinic-specific terminology in scheduling calls and insurance verification.
* **Medical contact centers** — Transcribe calls with correct medical vocabulary for downstream processing and quality assurance.

## Combine with other features

Medical Mode works alongside other streaming features. You can combine it with:

* [Streaming Diarization](/streaming/label-speakers-and-separate-channels) to identify who said what in clinical conversations
* [Keyterms Prompting](/streaming/prompting-and-keyterms) to further boost accuracy for specific medical terms unique to your use case

<Tabs>
  <Tab language="python" title="Python" default>
    ```python theme={null}
    CONNECTION_PARAMS = {
        "sample_rate": 16000,
        "speech_model": "universal-3-5-pro",
        "domain": "medical-v1",
        "speaker_labels": "true",
        "keyterms_prompt": json.dumps(["Lisinopril", "Metformin", "Humalog"])
    }
    ```
  </Tab>

  <Tab language="python-sdk" title="Python SDK">
    ```python theme={null}
    client.connect(
        StreamingParameters(
            sample_rate=16000,
            speech_model="universal-3-5-pro",
            domain="medical-v1",
            speaker_labels=True,
            keyterms_prompt=["Lisinopril", "Metformin", "Humalog"],
        )
    )
    ```
  </Tab>

  <Tab language="javascript" title="Javascript">
    ```javascript theme={null}
    const CONNECTION_PARAMS = {
      sample_rate: 16000,
      speech_model: "universal-3-5-pro",
      domain: "medical-v1",
      speaker_labels: true,
      keyterms_prompt: JSON.stringify(["Lisinopril", "Metformin", "Humalog"]),
    };
    ```
  </Tab>

  <Tab language="javascript-sdk" title="JavaScript SDK">
    ```javascript theme={null}
    const transcriber = client.streaming.transcriber({
      sampleRate: 16_000,
      speechModel: "universal-3-5-pro",
      domain: "medical-v1",
      speakerLabels: true,
      keytermsPrompt: ["Lisinopril", "Metformin", "Humalog"],
    });
    ```
  </Tab>
</Tabs>

## Configuration for medical audio

Medical conversations — such as clinical dictation, patient encounters, and ambient scribes — have different speech patterns than typical voice agent interactions. Clinicians often pause mid-sentence to think, review a chart, or formulate a diagnosis. The default turn detection settings are optimized for fast-paced voice agent dialogues and can incorrectly fragment these natural pauses into separate turns.

To prevent premature turn boundaries in medical audio, increase the silence thresholds:

```javascript theme={null}
const streamingConfig = {
  min_turn_silence: 800,
  max_turn_silence: 3600,
};
```

| Parameter          | Default                                              | Recommended for Medical | Why                                                                                             |
| ------------------ | ---------------------------------------------------- | ----------------------- | ----------------------------------------------------------------------------------------------- |
| `min_turn_silence` | `100` ms (U3 Pro) / `400` ms (Universal Streaming)   | `800` ms                | Gives clinicians time to pause mid-sentence without triggering a speculative end-of-turn check. |
| `max_turn_silence` | `1000` ms (U3 Pro) / `1280` ms (Universal Streaming) | `3600` ms               | Allows extended pauses for chart review or thinking without forcing a turn boundary.            |

<Info>
  These values match the [Conservative quick start configuration](/streaming/getting-started/transcribe-streaming-audio) on the turn detection page. You can further adjust them based on your specific workflow — for example, a real-time medical scribe may benefit from a lower `max_turn_silence` (around `2000` ms) than a dictation application.
</Info>

<Tabs>
  <Tab language="python" title="Python" default>
    ```python theme={null}
    CONNECTION_PARAMS = {
        "sample_rate": 16000,
        "speech_model": "universal-3-5-pro",
        "domain": "medical-v1",
        "min_turn_silence": 800,
        "max_turn_silence": 3600,
    }
    ```
  </Tab>

  <Tab language="python-sdk" title="Python SDK">
    ```python theme={null}
    client.connect(
        StreamingParameters(
            sample_rate=16000,
            speech_model="universal-3-5-pro",
            domain="medical-v1",
            min_turn_silence=800,
            max_turn_silence=3600,
        )
    )
    ```
  </Tab>

  <Tab language="javascript" title="Javascript">
    ```javascript theme={null}
    const CONNECTION_PARAMS = {
      sample_rate: 16000,
      speech_model: "universal-3-5-pro",
      domain: "medical-v1",
      min_turn_silence: 800,
      max_turn_silence: 3600,
    };
    ```
  </Tab>

  <Tab language="javascript-sdk" title="JavaScript SDK">
    ```javascript theme={null}
    const transcriber = client.streaming.transcriber({
      sampleRate: 16_000,
      speechModel: "universal-3-5-pro",
      domain: "medical-v1",
      minTurnSilence: 800,
      maxTurnSilence: 3600,
    });
    ```
  </Tab>
</Tabs>

<Warning>
  **Avoid setting end\_of\_turn\_confidence\_threshold to 0**

  If you are using a Universal Streaming model (not U3 Pro), do not set `end_of_turn_confidence_threshold` to `0`. This completely disables semantic turn detection and forces a turn boundary at every silence, which is especially harmful for medical audio where mid-sentence pauses are common. See [Turn detection](/streaming/getting-started/transcribe-streaming-audio) for details.
</Warning>

## HIPAA compliance

AssemblyAI offers a Business Associate Agreement (BAA) for customers who need to process Protected Health Information (PHI). AssemblyAI is SOC 2 Type 2, ISO 27001:2022, and PCI DSS v4.0 certified. Medical Mode does not change existing data handling or retention policies.

Paid customers can review and sign our standard online BAA self-serve, at no additional cost, from the [**Data Controls** page](https://www.assemblyai.com/dashboard/settings/data-controls) in the dashboard. You must have an upgraded (paid) account to see the BAA option. See [Data Controls](/data-controls#business-associate-agreement-baa) for details, or [contact sales](https://www.assemblyai.com/contact-sales) for enterprise pricing.