Multi-dimensional rehabilitation needs assessment and nursing plan generation method for head and neck tumor patients

Abstract

A multi-dimensional rehabilitation needs assessment and nursing plan generation method for head and neck tumor patients. The method sequentially executes the steps of multi-source report data collection, data preprocessing, multi-dimensional rehabilitation needs assessment, nursing plan generation and optimization, effectiveness validation, and rehabilitation outcome tracking and updating. Specifically, the method collects multi-dimensional report data, including imaging, laboratory, clinical medical records, patient subjective perceptions, and nutritional assessments. Preprocessing employs an improved BERT model to extract key information from unstmctured text and combines it with Z-score standardization to form a standardized dataset. The assessment relies on an index system covering sue dimensions (such as physiological and swallowing fimctions) and a multi-source data fusion model with an attention mechanism to achieve precise grading. Plan generation combines knowledge base matching and optimization based on patient individual characteristics. Effectiveness is validated through expert review and clinical pilot testing, and the plan is dynamically updated.