Gerardo C Fernandez

US Patent:

20130080134, Mar 28, 2013

Filed:

Jun 4, 2012

Appl. No.:

13/488176

Inventors:

Michael Donovan - Newton MA, US
Faisal Khan - Fishkill NY, US
Jason Alter - Carlsbad CA, US
Gerardo Fernandez - San Jose CA, US
Ricardo Mesa-Tejada - Pleasantville NY, US
Douglas Powell - Gettysburg PA, US
Valentina Bayer Zubek - Yonkers NY, US
Stefan Hamann - Cambridge MA, US
Jose Costa - Guilford CT, US

Assignee:

Fundação D. Anna Sommer Champalimaud e Dr. Carlos Montez Champalimaud - Lisboa

International Classification:

G06F 19/00

US Classification:

703 11

Abstract:

In general, one aspect of the subject matter described in this specification can be embodied in methods for assessing risk associated with prostate cancer, the methods including the actions of receiving patient data, comparing, with a processor executing code, the patient data to one or more predictive models, the one or more predictive models comprising at least one of (a) a disease progression (DP) model, the DP model being configured to predicts a likelihood of developing significant disease progression, and (b) a favorable pathology (FP) model, the FP model being configured to predict a likelihood of having organ confined, low grade disease in a prostatectomy, and outputting one or more results of the comparison Other embodiments of the various aspects include corresponding systems, apparatus, and computer program products.

US Patent:

20160253469, Sep 1, 2016

Filed:

May 13, 2016

Appl. No.:

15/154791

Inventors:

- Lisboa, PT
Faisal KHAN - Fishkill NY, US
Jason Alter - Carlsbad CA, US
Gerardo FERNANDEZ - San Jose CA, US
Ricardo MESA-TEJADA - Pleasantville NY, US
Douglas POWELL - Gettysburg PA, US
Valentina BAYER ZUBEK - Yonkers NY, US
Stefan HAMANN - Cambridge MA, US
Carlos CORDON-CARDO - New York NY, US
Jose COSTA - Guilford CT, US

International Classification:

G06F 19/00
G06N 7/00
G06F 17/30

Abstract:

In general, one aspect of the subject matter described in this specification can be embodied in methods for assessing risk associated with prostate cancer, the methods including the actions of receiving patient data, comparing, with a processor executing code, the patient data to one or more predictive models, the one or more predictive models comprising at least one of (a) a disease progression (DP) model, the DP model being configured to predicts a likelihood of developing significant disease progression, and (b) a favorable pathology (FP) model, the FP model being configured to predict a likelihood of having organ confined, low grade disease in a prostatectomy, and outputting one or more results of the comparison Other embodiments of the various aspects include corresponding systems, apparatus, and computer program products.