To establish a follow-up database for uterine adhesions and a library of biological specimens for Intrauterine Adhesion. 2. using epidemiological surveys and biological analyses to screen risk factors for the development and prognosis of Intrauterine Adhesion. 3. Predictive models based on clinical and biochemical indicators, specimen testing and hysteroscopic images are also combined with statistical analysis and machine learning algorithms to enable patients' risk stratification and prognostic assessment.