Rare diseases are characterized by low incidence rates, high heterogeneity, and significant genetic relevance, posing global challenges in clinical diagnosis and treatment, including delayed diagnosis and a scarcity of therapeutic options. Artificial intelligence (AI) technology offers novel solutions to address these challenges in the field of rare diseases. This paper explores the advancements in AI applications for rare diseases from two perspectives: auxiliary diagnosis and treatment decision-making. In terms of auxiliary diagnosis, AI can integrate superficial features, electronic health records, genomic data, and multi-modal data to achieve early and precise diagnosis. Regarding treatment decision-making, AI facilitates drug target discovery, drug repurposing, and the design of gene therapy vectors, thereby promoting the development and application of new treatments. Furthermore, this paper analyzes the challenges of AI in rare disease diagnosis and treatment concerning data, technical algorithms, and clinical application, and proposes future directions, including the construction of a collaborative data ecosystem, enhancement of algorithm interpretability, and improvement of regulatory frameworks.
From June 2002 to December 2023, there were 5 patients with criss-cross hearts admitted to the General Hospital of Northern Theater Command, including 3 males and 2 females, aged 1.5 to 25 years, and weighing 13-49 kg. There were 5 patients of atrioventricular position, 3 patients of right ventricular loop, 2 patients of left ventricular loop, 3 patients of normal atrioventricular connection, and 2 patients of inconsistent connection. Combined intracardiac malformations: 1 patient of simple ventricular septal defect combined with pulmonary hypertension, 1 patient of corrected transposition of the great arteries combined with ventricular septal defect, atrial septal defect, and pulmonary artery stenosis, 1 patient of corrected transposition of the great arteries combined with ventricular septal defect, atrial septal defect, and left atrioventricular valve insufficiency, and 2 patients of right ventricular double outlet combined with ventricular septal defect and pulmonary artery stenosis. The surgical methods included 2 patients of intracardiac anatomical correction, 1 patient of bidirectional vena cava pulmonary artery anastomosis, and 2 patients of total extracardiac ductal cava pulmonary artery anastomosis. All 5 patients were discharged smoothly.
