Explainable ai (XAI) platform for computational pathology

A pathological and explanatory technology, applied in the direction of calculation, computer components, detailed information related to graphical user interface, etc., can solve the problems that deep learning has not yet produced a proven advanced system, no pathologist, etc., to improve the quality of care , improve accuracy, minimize the effect of error

Pending Publication Date: 2022-01-04
SPINTELLX INC
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Despite being powerful in isolated, lower-level applications such as mitosis counting or cancer detection, deep learning has yet to produce proven, comprehensive, high-level systems
There is also fear and skepticism among pathologists about applying AI to pathology, and there is no consensus on how pathologists should oversee or work with computational pathology systems

Method used

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  • Explainable ai (XAI) platform for computational pathology
  • Explainable ai (XAI) platform for computational pathology
  • Explainable ai (XAI) platform for computational pathology

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Embodiment Construction

[0075] Pathology is considered the gold standard for medical diagnosis. Thus, pathologists have been conservative about making large practice changes. Computational pathology has received considerable attention, but also concern, since any error made by a computer may cause harm to a person and even pose a serious risk of loss of life. It is likely that xAI could facilitate the adoption of computational pathology because it not only efficiently presents the results but also explains how they were obtained. A human, usually a pathologist, can then easily determine whether the computer-generated results should be accepted or require further review. Releasable AI could also help advance scientific understanding of the pathologies that underlie cancer and other poorly understood diseases. It is important to note that we are using xAI to support pathologists in making efficient and more accurate "calls"

[0076] refer to Figure 1A to Figure 1C , the disclosure of information le...

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Abstract

Pathologists are adopting digital pathology for diagnosis, by using whole slide images (WSIs). Explainable Al (xAI) is a new approach to Al that can reveal underlying reasons for its results. As such, xAI can promote the safety, reliability, and accountability of machine learning for critical tasks such as pathology diagnosis. HistoMapr provides intelligent xAI guides for pathologists to improve the efficiency and accuracy of pathological diagnoses. HistoMapr can previews entire pathology cases' WSIs, identifies key diagnostic regions of interest (ROIs), determines one or more conditions associated with each ROI, provisionally labels each ROI with the identified conditions, and can triages them. The ROIs are presented to the pathologist in an interactive, explainable fashion for rapid interpretation. The pathologist can be in control and can access xAI analysis via a why interface. HistoMapr can track the pathologist's decisions and assemble a pathology report by using suggested, standardized terminology.

Description

[0001] Cross References to Related Applications [0002] This application claims priority and benefit to U.S. Provisional Patent Application No. 62 / 819,035, filed March 15, 2019, entitled "An Explainable AI (xAI) Platform for Computational Pathology," which is hereby incorporated by reference in its entirety The content is incorporated. technical field [0003] The present disclosure relates generally to an artificial intelligence (AI)-based system that performs image analysis and processing, and more particularly to a system that can assist in classifying one or more regions of an image based on corresponding conditions indicated by those regions, wherein , these conditions were determined using an interpretable artificial intelligence (xAI)-based platform. Background technique [0004] With the recent development of whole slide image (WSI) platforms for digital pathology, more and more pathologists have transitioned to viewing digital images of patient slides on computer ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H30/40G06K9/62G06T7/00
CPCG16H30/40G06T7/0012G06T2207/30024G06T2207/30068G06T2207/20081G06T2207/30242G06T2207/30016G06T2207/30061G06T2200/24G06T2207/30096G06F18/2431G06T2207/20084G06V20/69G06V20/695G06V20/698G06V10/7784
Inventor A·B·托松S·C·彻努博特拉J·L·法恩
Owner SPINTELLX INC
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