2results about How to "Avoid ignoring" patented technology

This disclosure provides a retrieval-enhanced diagnostic report generation method, apparatus, and electronic device, comprising: generating a preliminary diagnostic report for medical images of a case to be analyzed using a first preset large model; calculating the similarity between the preliminary diagnostic report and pre-stored diagnostic reports in a database to obtain similar cases; using the images of similar cases and their actual diagnostic reports as reference information, and inputting the medical images of the case to be analyzed and the reference information into a second preset large model to generate a final diagnostic report. This achieves a dual-driven diagnosis combining visual and semantic elements, accurately capturing pathological semantic relationships, avoiding the neglect of pathological diagnostic logic due to relying solely on visual features, and improving generalization ability.

The application discloses a distributed energy storage scheduling method based on a reinforcement learning algorithm, relates to the technical field of distributed energy storage, and comprises the following steps: an environment model of a battery swap station is constructed, and the scheduling management of the battery swap station is abstracted as a Markov decision process; wherein the environment model comprehensively considers battery charging and discharging characteristics, battery degradation and user charging and battery swap demands; an improved DDPG algorithm network architecture is introduced to strengthen the optimal scheduling strategy output by the Markov decision process; an experience replay pool is set, DDPG algorithm network parameters are updated, and the final optimal scheduling strategy is optimized and obtained. The application abstracts the scheduling management of the battery swap station as a Markov decision process, introduces the improved DDPG algorithm network architecture, and sets the experience replay pool, so that a small amount of abnormal sample experience is avoided from being ignored, the final optimal scheduling strategy can be suitable for a complex dynamic power grid environment, the uncertainty problem of the distributed energy storage power grid can be solved, and actual scheduling demands can be met.