Patents by Inventor Guangbin Huang

Guangbin Huang has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • METHOD OF PREDICTING ACUTE CARDIOPULMONARY EVENTS AND SURVIVABILITY OF A PATIENT
    Publication number: 20140257063
    Abstract: A method of producing an artificial neural network capable of predicting the survivability of a patient, including: storing in an electronic database patient health data comprising a plurality of sets of data, each set having at least one of a first parameter relating to heart rate variability data and a second parameter relating to vital sign data, each set further having 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 artificial neurons, each artificial neuron having at least one input with an associated weight; and training the artificial neural network using the patient health data such that the associated weight of the at least one input of each artificial neuron is adjusted in response to respective first, second and third parameters of different sets of data from the patient health data.
    Type: Application
    Filed: March 6, 2014
    Publication date: September 11, 2014
    Applicants: NANYANG TECHNOLOGICAL UNIVERSITY, SINGAPORE HEALTH SERVICES PTE LTD.
    Inventors: Marcus Eng Hock Ong, Zhiping Lin, Wee Ser, Guangbin Huang
  • METHOD OF PREDICTING ACUTE CARDIOPULMONARY EVENTS AND SURVIVABILITY OF A PATIENT
    Publication number: 20140187988
    Abstract: A method of producing an artificial neural network capable of predicting the survivability of a patient, including: storing in an electronic database patient health data comprising a plurality of sets of data, each set having at least one of a first parameter relating to heart rate variability data and a second parameter relating to vital sign data, each set further having 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 artificial neurons, each artificial neuron having at least one input with an associated weight; and training the artificial neural network using the patient health data such that the associated weight of the at least one input of each artificial neuron is adjusted in response to respective first, second and third parameters of different sets of data from the patient health data.
    Type: Application
    Filed: March 6, 2014
    Publication date: July 3, 2014
    Applicants: NANYANG TECHNOLOGICAL UNIVERSITY, SINGAPORE HEALTH SERVICES PTE LTD.
    Inventors: Marcus Eng Hock Ong, Zhiping Lin, Wee Ser, Guangbin Huang
  • Method of predicting acute cardiopulmonary events and survivability of a patient
    Patent number: 8668644
    Abstract: A method of producing an artificial neural network capable of predicting the survivability of a patient, including: storing in an electronic database patient health data comprising a plurality of sets of data, each set having at least one of a first parameter relating to heart rate variability data and a second parameter relating to vital sign data, each set further having 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 artificial neurons, each artificial neuron having at least one input with an associated weight; and training the artificial neural network using the patient health data such that the associated weight of the at least one input of each artificial neuron is adjusted in response to respective first, second and third parameters of different sets of data from the patient health data.
    Type: Grant
    Filed: April 23, 2013
    Date of Patent: March 11, 2014
    Assignees: Singapore Health Services Pte Ltd., Nanyang Technological University
    Inventors: Marcus Eng Hock Ong, Zhiping Lin, Wee Ser, Guangbin Huang
  • METHOD OF PREDICTING ACUTE CARDIOPULMONARY EVENTS AND SURVIVABILITY OF A PATIENT
    Publication number: 20130237776
    Abstract: A method of producing an artificial neural network capable of predicting the survivability of a patient, including: storing in an electronic database patient health data comprising a plurality of sets of data, each set having at least one of a first parameter relating to heart rate variability data and a second parameter relating to vital sign data, each set further having 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 artificial neurons, each artificial neuron having at least one input with an associated weight; and training the artificial neural network using the patient health data such that the associated weight of the at least one input of each artificial neuron is adjusted in response to respective first, second and third parameters of different sets of data from the patient health data.
    Type: Application
    Filed: April 23, 2013
    Publication date: September 12, 2013
    Applicants: NANYANG TECHNOLOGICAL UNIVERSITY, SINGAPORE HEALTH SERVICES PTE LTD.
    Inventors: Marcus Eng Hock Ong, Zhiping Lin, Wee Ser, Guangbin Huang
  • METHOD OF PREDICTING ACUTE CARDIOPULMONARY EVENTS AND SURVIVABILITY OF A PATIENT
    Publication number: 20110224565
    Abstract: According to embodiments of the invention, there is provided a method of producing an artificial neural network capable of predicting the survivability of a patient, the method including: storing in an electronic database patient health data, the patient health data comprising a plurality of sets of data, each set having at least one of a first parameter relating to heart rate variability data and a second parameter relating to vital sign data, each set further having 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 artificial neurons, each artificial neuron having at least one input with an associated weight; and training the artificial neural network using the patient health data such that the associated weight of the at least one input of each artificial neuron of the plurality of artificial neurons is adjusted in response to respective first, second and third parameters of different se
    Type: Application
    Filed: March 14, 2011
    Publication date: September 15, 2011
    Applicants: SINGAPORE HEALTH SERVICES PTE LTD., NANYANG TECHNOLOGICAL UNIVERSITY
    Inventors: Marcus Eng Hock Ong, Zhiping Lin, Wee Ser, Guangbin Huang