ABSTRACT
To investigate the characteristics of psychological symptoms in inflammatory bowel disease (IBD), to study the relationship between psychological symptoms and quality of life, and to provide some theoretical basis for the corresponding psychological treatment of IBD patients with psychiatric abnormalities. With the development of artificial intelligence (AI) and its gradual application to the medical field, it has brought new ideas to the medical development, and its research and application in IBD, including ulcerative colitis (UC) and Crohn's disease (CD), is increasing. Machine learning is used to select reasonable models and methods to help the prediction, diagnosis, treatment, and prognosis of IBD. In this study, we improved on the classical unidirectional LSTM model by adding backward and forward LSTM layers, designed a bidirectional LSTM model to improve the shortcomings of unidirectional LSTM with insufficient dependence on the posterior, introduced the contribution rate α to adjust the weight matrix of the forward LSTM layer and the backward LSTM layer, and experimentally verified the correctness and superiority of the proposed model. A total of 159 patients with IBD and 89 healthy people were collected and psychologically assessed using the general status questionnaire, the 90-item symptom checklist (SCL-90). Patients with IBD are prone to a combination of obsessive-compulsive, interpersonal, depressive, hostile, and other abnormal psychological symptoms, and their quality of life is significantly reduced; quality of life is mainly affected by disease condition, depression, interpersonal sensitivity, and paranoia, and patients in the active stage of the disease with heavy symptoms of depression, paranoia, and interpersonal sensitivity have low quality of life.