IP Library Patent Application 17877319
Patent Application
App. No. 17/877,319

SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES IN FORENSIC PATHOLOGY

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Patent No.
US None
App. No.
17/877,319
Abstract

A computer-implemented method for processing electronic medical images, the method including receiving images of at least one pathology specimen, the pathology specimen being associated with a patient. The system may determine, using a machine learning system and based on the electronic medical images, at least one contributing cause of death. The system may provide at least contributing cause of death.

Claims (34)

1 . A computer-implemented method for processing electronic medical images, comprising:

receiving a plurality of electronic medical images of at least one pathology specimen, the pathology specimen being associated with a patient;

determining, using a machine learning system and based on the electronic medical images, at least one contributing cause of death, wherein the machine learning system is trained using a plurality of electronic medical images; and

providing the at least one contributing cause of death for display to a user.

2 . The method of claim 1 , further including receiving an autopsy report and information relating to an age, ethnicity, ancillary test results, and/or an autopsy report of the patient.

3 . The method of claim 1 , further including detecting one or more salient region of each of the plurality of electronic medical images.

4 . The method of claim 3 , wherein the machine learning system only analyzes the salient regions of the plurality of electronic medical images.

5 . The method of claim 1 , wherein the machine learning system determines a numerical value score for each contributing cause of death.

6 . The method of claim 1 , further including marking the plurality of medical images to depict where evidence for the contributing cause of death is located.

7 . The method of claim 1 , wherein when more than one contributing cause of death is determined, ranking each contributing cause of death from most to least likely.

8 . The method of claim 1 , including determining and ranking which of the plurality of medical images provides the most evidence for the contributing cause of death.

9 . The method of claim 1 , including predicting, through the machine learning system, an organ that likely caused the death of the patient.

10 . The method of claim 1 , further comprising:

receiving a gross description, the gross description comprising data about the patient;

determining report metadata based on the gross description; and

wherein, the machine learning model uses the metadata and gross description, in addition to the received plurality of electronic medical images to predict a cause of death.

11 . The method of claim 1 , wherein the machine learning system outputs a vector and each place of the vector represents a potential cause of death, wherein each place of the vector represents a percent chance of a particular cause of death.

12 . A system for processing electronic medical images, the system comprising:

at least one memory storing instructions; and

at least one processor configured to execute the instructions to perform operations comprising:

receiving a plurality of electronic medical images of at least one pathology specimen, the pathology specimen being associated with a patient;

determining, using a machine learning system and based on the electronic medical images, at least on contributing cause of death, wherein the machine learning system is trained using a plurality of electronic medical images; and

providing the at least one contributing cause of death for display to a user.

13 . The system of claim 12 , further including receiving information relating to an age, ethnicity, ancillary test results, and/or an autopsy report of the patient.

14 . The system of claim 12 , further including detecting one or more salient region of each of the plurality of electronic medical images.

15 . The system of claim 14 , where the machine learning system only analyzes the salient regions of the plurality of electronic medical images.

16 . The system of claim 12 , wherein the machine learning system determines a numerical value score for each contributing cause of death.

17 . The system of claim 12 , further including marking the plurality of medical images to determine where evidence for the contributing cause of death is located.

18 . The system of claim 12 , wherein when more than one contributing cause of death is determined, ranking each contributing cause of death from most to least likely.

19 . The system of claim 12 , including determining and ranking which of the plurality of medical images provides the most evidence for the contributing cause of death.

20 . A non-transitory computer-readable medium storing instructions that, when executed by a processor, perform operations processing electronic medical images, the operations comprising:

receiving a plurality of electronic medical images of at least one pathology specimen, the pathology specimen being associated with a patient;

determining, using a machine learning system and based on the electronic medical images, at least on contributing cause of death, wherein the machine learning system is trained using a plurality of electronic medical images; and

providing the at least one contributing cause of a death for display to a user.

Assignments (3)
RELEASE OF SECURITY INTEREST Recorded May 14, 2026
From: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
To: PAIGE.AI, INC.
Reel/Frame 075589/0752 →
SECURITY INTEREST Recorded Oct 21, 2025
From: PAIGE.AI, INC.
To: ARES CAPITAL CORPORATION, AS COLLATERAL AGENT
Reel/Frame 073216/0876 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 1, 2022
From: KUNZ, JEREMY DANIEL; KANAN, CHRISTOPHER; GODRICH, RAN; RACITI, PATRICIA; FERSEL, MINDY
To: PAIGE.AI, INC.
Reel/Frame 060681/0746 →