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This paper presents a computational framework for detecting and interpreting dynamic team-process phases in collaborative virtual reality using late chunking and change-point detection to analyze temporal changes in team communication.
This paper introduces Feature Sufficiency Analysis (FSA), a framework to determine whether a subset of clinical features is sufficient for AI model predictions, with case studies in postoperative ventilation and mortality prediction.