TACL: Threshold-Adaptive Curriculum Learning Strategy for Enhancing Medical Text Understanding

TACL, or Threshold-Adaptive Curriculum Learning, is a novel framework introduced to enhance the understanding of medical texts, especially electronic medical records (EMRs), which are vital for patient care and clinical decision-making. The challenge lies in the unstructured nature and domain-specific language of these texts, which complicates automated understanding. Traditional methods often overlook the varying complexity of clinical records, limiting their effectiveness. TACL addresses this by categorizing data into difficulty levels and adjusting the training process accordingly. This progressive learning approach has shown significant improvements across various clinical tasks, including automatic ICD coding and readmission prediction, demonstrating its potential to advance healthcare analytics and decision-making. The application of TACL to multilingual medical data, including English and Chinese, further underscores its versatility and relevance in a global healthcare context.