Dataset shift is inevitable, but are you prepared to handle it in #PHI data? Our latest blog explores how dataset characteristics evolve over time and why monitoring distribution shifts is crucial for maintaining de-identification model performance. A #PHI detection model is only as reliable as the data it’s trained on, but what happens when new types of clinical notes—such as telehealth transcripts or handwritten documents—enter the pipeline? Without proactive monitoring, model performance can degrade, leading to compliance risks and inaccurate redactions. Read more: https://hubs.li/Q03b0Hn10 #DataPrivacy #DataAnonymization #DataProtection #largelanguagemodels?#LLMs?#HealthcareLLMs #GenerativeAI?#HealthcareAI #MedicalLLMs #MachineLearning #ResponsibleAI
