Identify if medical record is in a text message
using AI
Below is a free classifier to identify if medical record is in a text message. Just input your text, and our AI will predict if the medical record is present in the text message - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-medical-record-is-in-a-text-message", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/if-medical-record-is-in-a-text-message/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/if-medical-record-is-in-a-text-message/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict if the medical record is present in the text message.
This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Contains Medical Record and Does Not Contain Medical Record.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if the medical record is present in the text message).
Whether you're just curious or building if medical record is in a text message detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify if medical record is in a text message at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Telehealth Compliance Monitoring: This use case involves analyzing text messages sent between patients and healthcare providers to ensure that no medical records are shared inappropriately. By identifying messages that contain medical records, healthcare organizations can ensure compliance with HIPAA regulations and maintain patient confidentiality.
- Patient Messaging Filtering: The functionality can be utilized in patient messaging systems to filter and flag any messages containing medical records for further review. This helps healthcare providers prioritize sensitive communications and enhances data security by preventing unintentional sharing of sensitive information.
- Automated Medical Record Storage: This use case allows healthcare systems to automatically categorize and store text messages that contain medical records into designated secure databases. By streamlining the process of storing medical records, healthcare organizations can improve efficiency and minimize human error in record-keeping.
- Patient Education and Engagement: Medical facilities can use this function to gauge the nature of patient inquiries in text messages, ensuring that educational content is appropriately tailored. If a patient’s message contains a medical record, the system can trigger follow-up actions, such as scheduled consultations or customized educational material.
- Fraud Detection: This identifier can help detect fraudulent activities by monitoring text messages for unauthorized sharing of medical records. If messages that contain categorized medical information are identified between individuals not authorized for such communication, it can alert security teams for further investigation.
- Clinical Research Data Collection: Researchers can leverage the classification function to sift through vast amounts of messaging data related to clinical trials, identifying pertinent medical records. By doing this, they can enhance the quality of their research data and streamline the process of collecting evidence from real-world patient interactions.
- Integration with CRM Systems: Integrating this text classification function into Customer Relationship Management (CRM) systems can enhance patient relationship management by keeping sensitive communications secure. It allows healthcare organizations to track patient interactions while ensuring that any sensitive medical records in text messages are handled according to security protocols.