Real World Data

Healthcare Medical Clinical NLP

Streamline unstructured data to overcome everyday challenges. Simplify data analysis, derive greater insights, and deliver personalized care to patients with healthcare NLP.

Trusted By

Who We Are

Next-gen Healthcare AI

Over 80% of valuable healthcare information is trapped in unstructured text, making it difficult to access. Manual review of patient records is inefficient, costly, and time-consuming.

Uses Natural Language Processing (NLP) to understand medical data. It’s built on a large language model that’s been fine-tuned on a vast amount of real-world health data. This allows for high precision and speed in processing complex healthcare data. It provides an enhanced platform for custom model training, leading to improved outcomes, operational efficiency, and data security.

  • Large Language Model in Healthcare
  • Enhanced Annotation Services
  • Cloud Independence & On-Premise Hosting
  • Fixed Pricing, Unlimited Processing
  • Custom Model Training

Solutions

Advancing Healthcare Innovation

We create custom clinical NLP solutions tailored to your needs. Our technology includes NER, OCR, Generative AI, and Data De-identification. We empower healthcare providers to unlock the full potential of their medical data.

Custom APIs

Empower Your Healthcare Solutions

At HealthcareNLP, we go beyond offering pre-built APIs and solutions. We understand that every healthcare organization has unique requirements and specialized use cases. To cater to your specific needs, we are delighted to introduce our Custom APIs, a comprehensive and flexible offering that empowers you to harness the full potential of our platform and expertise.

PHI Entity Recognition API Benchmarking

To benchmark the Shaip API against the AWS API, precision, recall, and F-measure metrics were calculated, providing valuable insights into the performance of both systems.

Key MetricsRecall MetricsPrecision MetricsF1 Score Metrics
ShaipAmazonShaipAmazonShaipAmazon
Overall99.30%85.79%99.09%90.21%99.19%88.51%
Telephone92.00%73.68%95.83%8.05%93.88%14.51%
Season100.00%-66.67%-80.00%-
Room No.96.30%-92.86%-94.55%-
Person Name99.51%89.10%99.19%91.42%99.35%90.25%
Organization64.71%-78.57%-70.97%-
Location84.95%72.37%89.27%67.32%87.05%69.75%
Hospital93.70%-94.07%-93.89%-
ID99.34%63.66%99.01%80.11%99.17%70.94%
Date99.95%86.33%99.92%93.55%99.93%89.79%
Age98.52%72.78%93.78%72.35%96.09%72.57%

Case Studies

Licensing, De-identification, & Annotation

The client, a prominent healthcare entity, needed a NLP system to handle a large amount of oncology records. This case study details our work in improving the client’s research through precise data annotation, strict de-identification, & NLP, all in compliance with HIPAA regulations.