use_cases.rst

Use Cases of PyHealth

PyHealth enables various healthcare machine learning applications. Below are some practical use cases, categorized by data modality, each linked to an interactive Google Colab notebook.

Structured Data

Predicting Hospital Readmission

Hospital readmission prediction helps identify patients at high risk of returning to the hospital shortly after discharge. This can assist healthcare providers in taking preventive measures.

• [Colab Notebook](https://colab.research.google.com/drive/1bhCwbXce1YFtVaQLsOt4FcyZJ1_my7Cs?usp=sharing)

Drug Recommendation System

Personalized drug recommendation models can suggest appropriate medications based on a patient’s medical history, improving treatment outcomes.

• [Colab Notebook](https://colab.research.google.com/drive/10CSb4F4llYJvv42yTUiRmvSZdoEsbmFF?usp=sharing)

Length of Stay Prediction

Predicting hospital length of stay aids resource allocation, bed management, and patient care planning in hospitals.

• [Colab Notebook](https://colab.research.google.com/drive/1JoPpXqqB1_lGF1XscBOsDHMLtgvlOYI1?usp=sharing)

Mortality Prediction from ICU Data

Predicting ICU patient mortality using clinical data can help prioritize critical care and optimize resource usage.

• [Colab Notebook](https://colab.research.google.com/drive/1Qblpcv4NWjrnADT66TjBcNwOe8x6wU4c?usp=sharing)

Time-Series Data

Sleep Staging

Sleep staging classification uses EEG data to determine different sleep stages, aiding in the diagnosis and treatment of sleep disorders.

• [Colab Notebook](https://colab.research.google.com/drive/1mpSeNCAthXG3cqROkdUcUdozIPIMTCuo?usp=sharing)

Imaging Data

X-ray Classification

X-ray classification models can assist radiologists by automatically detecting abnormalities in chest X-rays and other radiographic images.

• [Colab Notebook](https://drive.google.com/file/d/1XokhV8dN3lis7gMdjpMhZBEGs03sus9R/view?usp=share_link)

Text Data

Medical Transcription Classification

Classifying medical transcriptions enables automated processing of clinical notes, improving documentation efficiency and accessibility.

• [Colab Notebook](https://drive.google.com/file/d/1JxQYEj94WjEsRifAOyEfrFWWIjqXxrqH/view?usp=share_link)

Each notebook provides step-by-step guidance on data processing, model training, and evaluation using PyHealth.