I need a comprehensive dataset to train a CNN algorithm for detecting patient-ventilator asynchronies (PVA). The data should be synthetically generated using Python. Dataset Requirements: - Types of Asynchronies: Trigger asynchrony, Flow asynchrony, Cycle asynchrony - Necessary Details: Occurrence frequency, Patient demographic info Ideal Skills and Experience: - Proficiency in Python - Experience in data synthesis and manipulation - Familiarity with CNNs and dataset requirements for machine learning - Background in medical data or ventilator mechanics is a plus Please ensure the dataset is large and varied enough for effective training.