Tutorial

We provide the following tutorials to help users get started with our PyTrial. After go through all these chapters, you will become the expert in AI for clinical trials and are ready to explore the frontier of this field. We are more than happy to welcome you to join us to revolutionize the drug development process via the cutting-edge AI technologies!

The principle of PyTrial

• Intro 1: Overview of PyTrial
• Intro 2: PyTrial API & Pipeline
• Intro 3: Basic Patient Data Class
• Intro 4: Basic Trial Data Class

Tutorials for each task

• Task 1: Individual Patient Outcome Prediction (tasks.indiv_outcome)
• Task 2: Clinical Trial Site Selection (tasks.site_selection)
• Task 3: Trial Outcome Prediction (tasks.trial_outcome)
• Task 4: Patient-Trial Matching (tasks.trial_patient_match)
• Task 5: Trial Similarity Search (tasks.trial_search)
• Task 6: Trial Patient Records Simulation (tasks.trial_simulation)

Additional utilities

• Misc 1: Load Preprocessed Demo Data
• Misc 2: Prepare Oncology Trial Patient Data
• Misc 3: Pretrained BERT Model
• Misc 4: ICD9 & 10 Knowledge Graph
• Misc 5: Drug Knowledge Graph