公开(公告)号：US20250095807A1

公开(公告)日：2025-03-20

申请号：US18883782

申请日：2024-09-12

Applicant: Oracle International Corporation

Inventor： Syed Najam Abbas Zaidi ,  Poorya Zaremoodi ,  Shiquan Yang ,  Nitika Mathur ,  Shubham Pawankumar Shah ,  Arash Shamaei ,  Sagar Kalyan Gollamudi

IPC: G16H10/60 ,  G10L15/26

Abstract: Techniques are disclosed for automatically generating prompts. A method comprises accessing first prompts, wherein each of the first prompts is a prompt for generating a portion of a SOAP note using a machine-learning model. For each respective first prompt of the first prompts: (i) using the respective first prompt to obtain a first result from a first machine-learning model, (ii) using the respective first prompt and the first result to obtain a second result from a second machine-learning model, the second result including an assessment of the first result, (iii) using the second result to obtain a third result from a third machine-learning model, the third result including a second prompt, (iv) setting the second prompt as the respective first prompt, (v) repeating steps (i)-(iv) a number of times to obtain a production prompt, (vi) adding the production prompt to a collection of prompts; and storing the collection of prompts.

公开(公告)号：US20250095806A1

公开(公告)日：2025-03-20

申请号：US18883595

申请日：2024-09-12

Applicant: Oracle International Corporation

Inventor： Syed Najam Abbas Zaidi ,  Shiquan Yang ,  Poorya Zaremoodi ,  Nitika Mathur ,  Shubham Pawankumar Shah ,  Arash Shamaei ,  Sagar Kalyan Gollamudi

IPC: G16H10/60 ,  G06N20/20

Abstract: Techniques are disclosed for automatically generating Subjective, Objective, Assessment and Plan (SOAP) notes. Particularly, techniques are disclosed for identifying entities for automatic SOAP note generation. A text transcript is accessed and segmented into portions. The text transcript can correspond to an interaction between a first entity and a second entity. Entities for the respective portions are identified using machine-learning models. A SOAP note is generated using the one or more machine-learning models and facts are derived from the text transcript based at least in-part on the entities. The SOAP note can be stored in a database in association with at least one of the first entity and the second entity.

公开(公告)号：US20250095798A1

公开(公告)日：2025-03-20

申请号：US18830972

申请日：2024-09-11

Applicant: Oracle International Corporation

Inventor： Arash Shamaei ,  Sagar Kalyan Gollamudi ,  Poorya Zaremoodi ,  Nitika Mathur ,  Shubham Pawankumar Shah ,  Syed Najam Abbas Zaidi ,  Shiquan Yang

IPC: G16H10/00

Abstract: Techniques are disclosed for automatically evaluating SOAP notes. A method comprises accessing a Subjective, Objective, Assessment and Plan (SOAP) note and a checklist that includes checklist facts; using a first machine-learning model prompt to extract SOAP note facts from the SOAP note; using one or more second machine-learning model prompts to generate feedback for the SOAP note, the feedback indicating whether individual checklist facts are supported by at least one of the SOAP note facts, and whether individual SOAP note facts are supported by at least one of the checklist facts; and generating a score for the SOAP note based on the feedback.

公开(公告)号：US20240062011A1

公开(公告)日：2024-02-22

申请号：US18351680

申请日：2023-07-13

Applicant: Oracle International Corporation

Inventor： Aashna Devang Kanuga ,  Cong Duy Vu Hoang ,  Mark Edward Johnson ,  Vasisht Raghavendra ,  Yuanxu Wu ,  Steve Wai-Chun Siu ,  Nitika Mathur ,  Gioacchino Tangari ,  Shubham Pawankumar Shah ,  Vanshika Sridharan ,  Zikai Li ,  Diego Andres Cornejo Barra ,  Stephen Andrew McRitchie ,  Christopher Mark Broadbent ,  Vishal Vishnoi ,  Srinivasa Phani Kumar Gadde ,  Poorya Zaremoodi ,  Thanh Long Duong ,  Bhagya Gayathri Hettige ,  Tuyen Quang Pham ,  Arash Shamaei ,  Thanh Tien Vu ,  Yakupitiyage Don Thanuja Samodhve Dharmasiri

IPC: G06F40/295 ,  G06F40/284 ,  G06F40/211 ,  G06F40/35

CPC classification number: G06F40/295 ,  G06F40/284 ,  G06F40/211 ,  G06F40/35

Abstract: Techniques are disclosed herein for using named entity recognition to resolve entity expression while transforming natural language to a meaning representation language. In one aspect, a method includes accessing natural language text, predicting, by a first machine learning model, a class label for a token in the natural language text, predicting, by a second machine-learning model, operators for a meaning representation language and a value or value span for each attribute of the operators, in response to determining that the value or value span for a particular attribute matches the class label, converting a portion of the natural language text for the value or value span into a resolved format, and outputting syntax for the meaning representation language. The syntax comprises the operators with the portion of the natural language text for the value or value span in the resolved format.

公开(公告)号：US20250118398A1

公开(公告)日：2025-04-10

申请号：US18884459

申请日：2024-09-13

Applicant: Oracle International Corporation

Inventor： Shubham Pawankumar Shah ,  Syed Najam Abbas Zaidi ,  Xu Zhong ,  Poorya Zaremoodi ,  Srinivasa Phani Kumar Gadde ,  Arash Shamaei ,  Ganesh Kumar ,  Thanh Tien Vu ,  Nitika Mathur ,  Chang Xu ,  Shiquan Yang ,  Sagar Kalyan Gollamudi

IPC: G16H10/60 ,  G06N20/00

Abstract: Techniques are disclosed for automatically generating Subjective, Objective, Assessment and Plan (SOAP) notes. Particularly, techniques are disclosed for training data collection and evaluation for automatic SOAP note generation. Training data is accessed, and evaluation process is performed on the training data to result in evaluated training data. A fine-tuned machine-learning model is generated using the evaluated training data. The fine-tuned machine-learning model can be used to perform a task associated with generating a SOAP note.

公开(公告)号：US20250095804A1

公开(公告)日：2025-03-20

申请号：US18830934

申请日：2024-09-11

Applicant: Oracle International Corporation

Inventor： Syed Najam Abbas Zaidi ,  Shiquan Yang ,  Poorya Zaremoodi ,  Nitika Mathur ,  Shubham Pawankumar Shah ,  Arash Shamaei ,  Sagar Kalyan Gollamudi

IPC: G16H10/60 ,  G06F40/295

Abstract: Techniques are disclosed for automatically generating Subjective, Objective, Assessment and Plan (SOAP) notes. Particularly, techniques are disclosed for automatic SOAP note generation using task decomposition. A text transcript is accessed and segmented into portions. The text transcript can correspond to an interaction between a first entity and a second entity. Machine-learning model prompts are used to extract entities and facts for the respective portions and generate SOAP note sections based at least in-part on the facts. A SOAP note is generated by combining the SOAP note sections. The SOAP note can be stored in a database in association with at least one of the first entity and the second entity.

公开(公告)号：US20250095803A1

公开(公告)日：2025-03-20

申请号：US18829834

申请日：2024-09-10

Applicant: Oracle International Corporation

Inventor： Syed Najam Abbas Zaidi ,  Shiquan Yang ,  Poorya Zaremoodi ,  Nitika Mathur ,  Shubham Pawankumar Shah ,  Arash Shamaei ,  Sagar Kalyan Gollamudi

IPC: G16H10/60 ,  G06F40/205 ,  G06F40/295

Abstract: Techniques are disclosed for automatically generating Subjective, Objective, Assessment and Plan (SOAP) notes. Particularly, techniques are disclosed for identifying entities for automatic SOAP note generation. A text transcript is accessed and segmented into portions. The text transcript can correspond to an interaction between a first entity and a second entity. One or more entities for the respective portions are identified using one or more machine-learning models. Facts are from the respective portions using the one or more machine-learning models based at least in-part on the context of the respective portions. A SOAP note is generated using the one or more machine-learning models and based at least in-part on the facts. The SOAP note can be stored in a database in association with at least one of the first entity and the second entity.