Identify medical terms in text
Generate medical reports from patient data
Predict Alzheimer's risk based on demographics and health data
Classify chest X-rays to detect diseases
Consult medical information with a chatbot
Answer medical questions using real-time AI
Classify medical images into 6 categories
Find the right medical specialist for your symptoms
Store and analyze lung sounds
Answer medical questions and get advice
Explore and analyze medical data through various tools
Identify diabetic retinopathy stages from retinal images
Predict brain tumor type from MRI images
Clinical AI Apollo Medical NER is a specialized Named Entity Recognition (NER) tool designed for the medical domain. It is engineered to identify and extract medical entities such as diseases, symptoms, medications, and procedures from unstructured text data. This solution is particularly useful for processing clinical notes, medical reports, and other healthcare-related documents, enabling efficient data analysis and decision-making.
What types of entities can Apollo Medical NER identify?
Apollo Medical NER can identify a wide range of medical entities, including diseases, symptoms, medications, procedures, anatomical terms, and lab tests. Customization options allow you to expand this list based on your specific needs.
Is Apollo Medical NER suitable for real-time applications?
Yes, Apollo Medical NER is designed to process text data quickly, making it suitable for real-time applications such as emergency room notes or live patient consultations.
How accurate is Apollo Medical NER?
Apollo Medical NER achieves high accuracy in medical entity recognition, with precision and recall rates that exceed many industry standards. Accuracy can be further improved by fine-tuning the model for your specific use case.