The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 29, 2016

Filed:

Dec. 12, 2014
Applicants:

Singapore Health Services Pte Ltd., Singapore, SG;

Nanyang Technological University, Singapore, SG;

Inventors:

Marcus Eng Hock Ong, Singapore, SG;

Zhiping Lin, Singapore, SG;

Wee Ser, Singapore, SG;

Guangbin Huang, Singapore, SG;

Assignees:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); A61B 5/0205 (2006.01); A61B 5/1455 (2006.01); A61B 5/024 (2006.01); A61B 5/01 (2006.01); A61B 5/04 (2006.01); A61B 5/0402 (2006.01); A61B 5/0456 (2006.01); G06F 19/00 (2011.01); A61B 5/021 (2006.01); A61B 5/08 (2006.01); A61B 5/0468 (2006.01);
U.S. Cl.
CPC ...
A61B 5/7264 (2013.01); A61B 5/01 (2013.01); A61B 5/0205 (2013.01); A61B 5/02055 (2013.01); A61B 5/02405 (2013.01); A61B 5/0402 (2013.01); A61B 5/04014 (2013.01); A61B 5/0456 (2013.01); A61B 5/14551 (2013.01); A61B 5/4824 (2013.01); A61B 5/4836 (2013.01); A61B 5/6801 (2013.01); A61B 5/7275 (2013.01); A61B 5/742 (2013.01); G06F 19/345 (2013.01); A61B 5/021 (2013.01); A61B 5/0468 (2013.01); A61B 5/0816 (2013.01);
Abstract

A method of predicting survivability of a patient. The method includes storing in an electronic database patient health data comprising a plurality of sets of data, each set having a first parameter relating to heart rate variability data including at least one of ST segment elevation and depression, a second parameter relating to vital sign data, and a third parameter relating to patient survivability; providing a network of nodes interconnected to form an artificial neural network, the nodes comprising a plurality of neurons, each having at least one input with an associated weight; and training the neural network using the patient health data such that the associated weight of the at least one input of each neuron is adjusted in response to respective first, second and third parameters of different sets of data from the patient health data, such that the neural network is trained to produce a prediction on the survivability of a patient within the next 72 hours.


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