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公开(公告)号：US20250095834A1
公开(公告)日：2025-03-20
申请号：US18883923
申请日：2024-09-12
Applicant: Oracle International Corporation
Inventor： Jobinesh Purushothaman Manakkattil , Salman Saleem Sheikh , Frank Nimphius , Tamer Abdelkareem Qumhieh , Edward E. Wong , Abhinav Vasu Rawat
Abstract: Techniques are disclosed for assisting healthcare providers with common clinical tasks by way of a clinical software application that can be installed on and utilized from various client computing devices. The clinical software application(s) can enable a healthcare provider to record conversations with patients, dictate in natural language, generate patient notes, populate patient records, and perform numerous other clinical functions. Task entries to schedule such tasks may be generated at the express direction of an end user, or one or more machine-learning models may be used to analyze text transcribed from spoken conversations, to identify one or more tasks from dialogue within the text, and to create corresponding task entries. Notification configuration entries may be created and associated with task entries, and may be used to trigger sending of notifications for scheduled tasks at appropriate times. An end user interaction with a notification may initiate a conversation with a digital assistant.
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公开(公告)号：US20250094804A1
公开(公告)日：2025-03-20
申请号：US18883407
申请日：2024-09-12
Applicant: Oracle International Corporation
Inventor： Shashi Prasad Suravarapu , Amitabh Saikia , Srinivasa Phani Kumar Gadde , Diego Andres Cornejo Barra , Cody Nicholas Maheu , Yuanxu Wu , Laukik Satish Mujumdar , Daniel Bruce Carter , Zachary Jon-Christian Medeck , Jobinesh Purushothaman Manakkattil , Sangeet Dahal , Shweta Shyamsunder Gupta
IPC: G06N3/082 , G06N3/0455
Abstract: Techniques are disclosed for providing an authenticated model customization for a machine-learning model. A cloud service provider platform accesses a message including, at least, timestamp data and user identification data. A training group of data entities is identified based on the data in the message. A training dataset is determined based on the training group of data entities. A machine-learning model is modified based on the training dataset. The modified machine-learning model is provided during an authenticated network session associated with the user identification data. In some embodiments, the modification of the machine-learning model is removed based on a determination that the authenticated network session had ended.
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公开(公告)号：US20250095843A1
公开(公告)日：2025-03-20
申请号：US18830781
申请日：2024-09-11
Applicant: Oracle International Corporation
Inventor： Jobinesh Purushothaman Manakkattil , Shashi Prasad Suravarapu , Tamer Qumhieh , Edward E. Wong , Jayabratha Saha
Abstract: Techniques are disclosed for assisting healthcare providers with common clinical tasks by way of a clinical software application that can be installed on and utilized from various client computing devices. The clinical software application(s) can enable a healthcare provider to record conversations with patients, dictate in natural language, generate patient notes, populate patient records, schedule tasks and generate task notifications, and perform numerous other clinical functions. A state of the application executing on the client computing devices can be centrally and remotely controlled by a cloud service provider platform. When a user is logged in to both a mobile client computing device and a desktop client computing device, a state of both applications can be concurrently controlled by the cloud service provider platform, and the applications can be linked and synchronized to provide the end user with a seamless experience when moving between the applications.
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