semvec/pypi-packages huggingface dataset:
tpeai 0.2.0
A Python package to differentiate between tuberculous and non-tuberculous pleural effusion using ChatGPT-4 with biochemistry and blood cell analysis data.
Requires Python: <4.0,>=3.9

This Python package is designed to quickly differentiate between tuberculous pleural effusion and non-tuberculous pleural effusion by leveraging the predictive power of ChatGPT-4. 
By inputting a set of key variables related to the patient's biochemistry and blood cell analysis, the model can provide an intelligent prediction. The required variables include:

- Pleural fluid biochemistry: ADA, total protein, albumin
- Blood cell analysis: lymphocyte count, neutrophil percentage, monocyte percentage, neutrophil count
- Patient's age

By using these inputs, the model makes a prediction through ChatGPT-4, assisting clinicians in promptly identifying the type of pleural effusion, thereby supporting more informed diagnostic and treatment decisions.