AUTOMATED TRANSLATION OF DESIGN SPECIFICATIONS OF ELECTRONIC CIRCUITS

    公开(公告)号:US20250068846A1

    公开(公告)日:2025-02-27

    申请号:US18941768

    申请日:2024-11-08

    Applicant: Synopsys, Inc.

    Abstract: Embodiments relate to a system for translating design specifications of an electronic circuit. In one embodiment, the design specification is parsed to identify one or more sentences. From the one or more identified sentences, the system extracts semantic concepts. Additionally, for each sentence of the one or more identified sentences, the system determines whether the sentence is translatable. If a target sentence is translatable, the system generates a parse tree for the target sentence, and generates a probabilistic shift-reduce schedule for the generated parse tree. Using the generated probabilistic shift-reduce schedule and optionally the generated parse tree, the system generates code for verifying the condition specified in the target sentence. In some embodiments, to generate the code, the system parses the target sentence using the generated probabilistic shift-reduce schedule.

    SYSTEM AND METHOD FOR ARTIFICIAL INTELLIGENCE-BASED DIAGNOSTIC AND/OR TREATMENT GUIDANCE FOR PATIENTS

    公开(公告)号:US20250054633A1

    公开(公告)日:2025-02-13

    申请号:US18930520

    申请日:2024-10-29

    Abstract: A system and method provide artificial intelligence (AI)-based diagnostic guidance for a patient. The system receives captured radiological scan images of the patient, and input components such as results of physical examination of the patient and laboratory data of the patient. The system provides patient imaging information based on the recognized patterns of the received radiological scan images and the three-dimensional reconstructed scans, identifies problems based on predetermined AI criteria and deep-learning based on patient-specific patterns, responses, and the input components, determines risk factors of the patient which cause heath issues, provides probability estimation of diagnoses that predict probability of occurrence of the health issues to the patient based on the risk factors of the patient, prioritize the problems to a hot list based on the probability estimation of diagnoses.

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