You will get Clinical Named Entity Recognition (NER) – Automating Medical Text Analysis

Name: You will get Clinical Named Entity Recognition (NER) – Automating Medical Text Analysis
Availability: InStock

Maria A.

Maria A.

Project details

My project demonstrates expertise in Natural Language Processing (NLP) for healthcare. I built a Clinical Named Entity Recognition (NER) model that automatically extracts medical entities such as diseases, medications, and treatments from unstructured text. Unlike generic NLP models, this solution is tailored for the clinical domain, delivering higher accuracy and practical outputs ready for real-world use.

AI Development Type

Deep Learning, Model Tuning

AI Tools

PyTorch

AI Development Language

Python

What's included

Service Tiers	Starter $35	Standard $110	Advanced $170
Delivery Time	3 days	5 days	7 days
Number of Revisions	1	1	2
AI Model Integration
Detailed Code Comments	-	-	-
Knowledge Graph	-	-	-
Model Documentation	-	-
Ontology	-	-	-
Source Code	-	-	-
Taxonomy	-	-	-

About Maria

AI & Machine Learning, Artificial Intelligence

Cairo, Egypt - 12:19 pm local time

I build end-to-end AI solutions that help businesses turn data into measurable results. With deep expertise in machine learning, NLP, and generative AI, paired with strong DevOps skills, I design high-accuracy models and deploy them into production through scalable pipelines using Docker, Kubernetes, and CI/CD. My focus is on impact: cutting operational costs, boosting efficiency, and unlocking new revenue streams by turning cutting-edge AI research into practical, business-ready systems.

Steps for completing your project

After purchasing the project, send requirements so Maria can start the project.

Delivery time starts when Maria receives requirements from you.

Maria works on your project following the steps below.

Revisions may occur after the delivery date.

Data review

I review your text samples and confirm the categories/entities to include.