Shenzhen Mindray Bio-Medical Electronics has been granted a patent for a method that utilizes ultrasound imaging and ancillary information to predict disease states in subjects. The method involves comparing qualitative measurements to predetermined standards and correlating these with previous disease measurements to derive predictive values. GlobalData’s report on Shenzhen Mindray Bio-Medical Electronics gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Shenzhen Mindray Bio-Medical Electronics, AI-assisted ultrasonography was a key innovation area identified from patents. Shenzhen Mindray Bio-Medical Electronics's grant share as of June 2024 was 37%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting disease states using ultrasound imaging and measurements
The patent US12042333B2 outlines a method and system for predicting the presence or progression of a disease state in a subject using ultrasound imaging and various qualitative and quantitative measurements. The method involves identifying qualitative measurements through ultrasound, comparing these measurements to predetermined standards to derive initial values, and correlating this information with previous disease measurements. The final value, which is crucial for predicting disease states, can be determined using additional imaging modalities, raw data, or machine-learning algorithms. The previous measurements can include a range of data from ultrasound techniques, core biopsies, blood pressure, metabolic rates, and other diagnostic methods.
The system described in the patent comprises processors and computer-readable storage that execute instructions to perform the outlined operations. It emphasizes the integration of various imaging modalities, such as X-rays and MRI, alongside ultrasound data to enhance the predictive accuracy regarding disease states. The use of machine-learning algorithms is also highlighted, with various techniques such as decision trees and artificial neural networks being applicable for refining predictions. This comprehensive approach aims to improve diagnostic capabilities by leveraging both qualitative and quantitative data, ultimately facilitating better patient outcomes through informed medical decisions.
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