Personalized Medical Imaging Scheduling Platform

Publication ID: 24-11857804_0010_PTD

Published: October 28, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Personalized Medical Imaging Scheduling Platform,” Published Technical Disclosure No. 24-11857804_0010_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857804_0010_PTD

This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,804.

Summary of the Inventive Concept

A next-generation medical imaging scheduling system leveraging AI-driven predictive modeling, real-time treatment response data, and comprehensive patient profiles to optimize imaging schedules for individual patients, revolutionizing medical imaging decision support.

Background and Problem Solved

The original patent addressed the need for determining medical imaging schedules for subjects receiving treatment at a target site. However, it relied on static data and limited input parameters. The new inventive concept tackles the limitations of the original patent by integrating real-time treatment response data, machine learning, and electronic health records to provide personalized and adaptive imaging schedules.

Detailed Description of the Inventive Concept

The proposed system comprises a neural network module trained on historical treatment response data to predict optimal imaging times for a subject. A treatment planning module generates personalized treatment plans based on the predicted imaging times. A decision support module provides imaging schedule recommendations to healthcare professionals. The system can be implemented as a cloud-based platform, allowing for seamless integration with electronic health records and real-time data analytics. The method for optimizing medical imaging schedules uses real-time treatment response data to update a predictive model, generating personalized imaging schedules for each subject.

Novelty and Inventive Step

The new claims introduce the use of machine learning, real-time treatment response data, and electronic health records to personalize medical imaging schedules, which is a significant departure from the original patent's reliance on static data and limited input parameters. The inventive step lies in the integration of these components to provide adaptive and optimal imaging schedules.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include using different machine learning algorithms, incorporating additional data sources such as genomic data, or implementing the system as a standalone device. Variations could include adapting the system for use in different medical specialties or integrating it with existing hospital information systems.

Potential Commercial Applications and Market

The personalized medical imaging scheduling platform has significant commercial potential in the healthcare industry, particularly in hospitals and imaging centers. The market for medical imaging decision support systems is growing rapidly, and this inventive concept is poised to revolutionize the field by providing more accurate and personalized imaging schedules.

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Medical imaging decision support systems, specifically involving treatment response tracking, predictive modeling, and personalized medical scheduling. Requires expertise in medical informatics, machine learning, data analytics, and clinical workflow optimization

Person of Ordinary Skill (PHOSITA) Profile

A professional with advanced degrees in biomedical engineering, computer science, or medical informatics, possessing knowledge of machine learning techniques, medical imaging technologies, and healthcare data integration strategies

Obviousness Rationale

A PHOSITA would recognize that applying machine learning and real-time data analytics to the existing medical imaging scheduling framework represents a predictable technological evolution. The source patent's foundational approach of personalized medical imaging scheduling provides a clear template for integrating advanced computational techniques. The proposed variations represent straightforward technological improvements using well-established machine learning and data integration methodologies.

Obvious Combinations & Variations

Source Patent Element

Method for determining medical imaging schedule based on blood panel and initial imaging data

PTD Variation

Neural network module trained on historical treatment response data to predict optimal imaging times

Obviousness Reasoning

Applying machine learning to existing medical scheduling approaches is a known technique for improving predictive accuracy, representing an obvious design choice for a PHOSITA seeking to enhance decision support systems

Source Patent Element

Obtaining clinical information and treatment details for scheduling

PTD Variation

Comprehensive patient profile integration with electronic health records

Obviousness Reasoning

Expanding data sources for medical scheduling is a predictable solution for increasing precision, utilizing standard healthcare data integration techniques

Source Patent Element

Imaging modality selection for medical scheduling

PTD Variation

Cloud-based platform analyzing treatment response data across multiple healthcare institutions

Obviousness Reasoning

Scaling medical decision support systems through cloud infrastructure and multi-institutional data analysis represents a standard technological progression in healthcare informatics

Source Patent Element

Treatment response tracking methodology

PTD Variation

Real-time treatment response data used to dynamically update predictive modeling

Obviousness Reasoning

Implementing adaptive machine learning models to continuously refine medical scheduling represents an obvious extension of existing predictive healthcare technologies

Source Patent Element

Medical imaging scheduling based on multiple input parameters

PTD Variation

Recommendation engine generating personalized imaging schedule recommendations

Obviousness Reasoning

Creating intelligent decision support systems that provide personalized recommendations is a predictable application of machine learning in medical technology

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857804 and the disclosed technological variations, a person of ordinary skill in the art would find the proposed medical imaging scheduling innovations obvious and lacking inventive step. The combination of existing medical scheduling methodologies with machine learning, real-time data analytics, and comprehensive patient profiling represents a predictable technological progression that would be readily conceived by a skilled practitioner in medical informatics and computational healthcare technologies.

Original Patent Information

Patent Number	US 11,857,804
Title	Determining a medical imaging schedule
Assignee(s)	Koninklijke Philips N.V.