3 results about "Treatment characteristics" patented technology

The present application belongs to the tumor precision medicine and artificial intelligence medical technology field, and particularly relates to a non-small cell lung cancer neoadjuvant immunotherapy efficacy prediction method based on transfer learning. The method first pretreats the non-small cell lung cancer immunotherapy cohort and the neoadjuvant immunotherapy cohort, selects immunotherapy and neoadjuvant immunotherapy characteristic genes, and based thereon, carries out deep learning training on the immunotherapy cohort to obtain a basic model, finally, the basic model is fine-tuned to the neoadjuvant immunotherapy training data set through transfer learning, and finally used to the neoadjuvant immunotherapy cohort to predict the neoadjuvant immunotherapy effect. The present application improves the stability and generalization ability of the model in the small sample neoadjuvant treatment scene through gene selection and transfer fine-tuning, and can be used for clinical auxiliary decision and population stratification.

The application relates to the technical field of electric digital data processing, and discloses a big data fast indexing and querying system based on general surgery diagnosis and treatment characteristics, which comprises a data stream acquisition module, a topological sequence reorganization module, a physical space mapping module, an index key synthesis module and a preloading execution engine; the topological sequence reorganization module analyzes heterogeneous diagnosis and treatment data streams and reorganizes the data streams into logically continuous patient whole-course data aggregates; the physical space mapping module sequentially maps the aggregates to a continuous physical address space of a bottom-layer storage; the index key synthesis module generates composite index items according to physical address offsets among data blocks; and the preloading execution engine drives the bottom-layer storage to burst read, the application converts cross-modal diagnosis and treatment correlation queries into one-way sequential reading of the storage, reduces the track delay and access overhead in the searching process, and guarantees the searching response delay certainty under the condition that the data volume continuously grows.

The application discloses a cancer patient psychological health evaluation and intervention method and system, and the method comprises the following steps: acquiring community interaction behavior data and clinical diagnosis and treatment characteristic data of a target user on a platform; performing natural language processing and voice emotion recognition on the community interaction behavior data, and extracting original emotion characteristics; generating a current physiological state baseline and a treatment side effect expected window of the target user based on the clinical diagnosis and treatment characteristic data; inputting the original emotion characteristics into a joint analysis model, weighting and correcting original emotion characteristic values by using the physiological state baseline and the treatment side effect expected window, and calculating a psychological health index; comparing the dynamic psychological health index with a preset risk threshold, determining a psychological health risk level of the user, and triggering a corresponding grading intervention mechanism. The application can accurately distinguish between physiological distress and pathological depression, and realizes dynamic monitoring and accurate management of the psychological state of a cancer patient in an off-hospital rehabilitation period.