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Patent Application: Inferring Patient Condition Using Machine Learning

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Summary

The USPTO has published a patent application (US20260088175A1) filed by Hill-Rom Services, Inc. The application details a machine learning system designed to infer a patient's condition using sensor data and response variable data. This technology aims to improve patient monitoring and diagnostics.

Published by USPTO on changeflow.com . Detected, standardized, and enriched by GovPing. Review our methodology and editorial standards .

What changed

This document is a published patent application from the USPTO, specifically application US20260088175A1, filed by Hill-Rom Services, Inc. The application describes a machine learning system that utilizes sensor data from patient-associated products and response variable data to train an inference model. This model is intended to infer a patient's actual condition based on the collected sensor data.

As a patent application, this document does not impose immediate regulatory obligations or compliance deadlines on regulated entities. However, it signals potential future technological advancements in patient monitoring and diagnostics within the healthcare sector. Companies involved in health informatics, medical devices, and AI-driven healthcare solutions should be aware of this development as it may influence future product development and intellectual property landscapes.

Archived snapshot

Mar 26, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Applications

TECHNOLOGIES FOR INFERRING A PATIENT CONDITION USING MACHINE LEARNING

Application US20260088175A1 Kind: A1 Mar 26, 2026

Assignee

Hill-Rom Services, Inc.

Inventors

Timothy J. Receveur, Yongji Fu, Aziz A. Bhai

Abstract

A machine learning compute device may include circuitry configured to obtain sensor data from a product associated with a patient. The circuitry may also be configured to obtain response variable data indicative of an actual condition of the patient associated with the sensor data. Additionally, the circuitry may be configured to train, based on the response variable data and the sensor data, an inference model to infer the actual condition of the patient from the sensor data.

CPC Classifications

G16H 50/20 A61B 5/0077 A61B 5/1115 A61B 5/1121 A61B 5/1128 A61B 5/6892 A61B 5/7203 A61B 5/725 A61B 5/7267 A61G 7/05 G06N 20/00 G16H 10/60 G16H 40/67 A61B 5/447 A61B 2562/0219 A61B 2562/0252 A61G 2203/32 A61G 2203/34 A61G 2203/36 A61G 2203/44 G16H 40/40

Filing Date

2025-12-02

Application No.

19405555

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Named provisions

Assignee Inventors Abstract CPC Classifications

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Classification

Agency
USPTO
Published
December 2nd, 2025
Instrument
Notice
Legal weight
Non-binding
Stage
Draft
Change scope
Minor
Document ID
US20260088175A1

Who this affects

Applies to
Healthcare providers Medical device makers
Industry sector
3345 Medical Device Manufacturing 6211 Healthcare Providers 3254.1 Biotechnology
Activity scope
Patient Monitoring Medical Diagnostics
Geographic scope
United States US

Taxonomy

Primary area
Healthcare
Operational domain
IT Security
Topics
Artificial Intelligence Data Privacy

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