Neural network for glucose therapy recommendation
First Claim
Patent Images
1. A neural network device, comprising:
- an input layer configured to accept N input signals;
one or more “
i”
hidden layers having memory;
at least one output layer;
at least one neuron “
Ylayer”
within each layer, where “
layer”
is the layer defined as “
input”
, “
hiddeni”
or “
output”
; and
one or more memory structures configured to;
a) store a recursive memory of input signals past, and b) allow for at least one time series prediction of a response;
wherein one or more memory structures are included in both the input and hidden layers; and
wherein the device is configured to be a time-lagged feed forward neural network device for predicting analyte levels in a sample or a subject in need thereof.
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Abstract
A multifunctional neural network system for prediction which includes memory components to store previous values of data within a network. The memory components provide the system with the ability to learn relationships/patterns existent in the data over time.
32 Citations
20 Claims
-
1. A neural network device, comprising:
-
an input layer configured to accept N input signals; one or more “
i”
hidden layers having memory;at least one output layer; at least one neuron “
Ylayer”
within each layer, where “
layer”
is the layer defined as “
input”
, “
hiddeni”
or “
output”
; andone or more memory structures configured to;
a) store a recursive memory of input signals past, and b) allow for at least one time series prediction of a response;wherein one or more memory structures are included in both the input and hidden layers; and wherein the device is configured to be a time-lagged feed forward neural network device for predicting analyte levels in a sample or a subject in need thereof. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
-
-
18. A device for forecasting one or more of:
- elevated glucose levels or lack of optimal glycemic control, in a subject in need thereof, comprising;
providing an input layer designed to accept N input signals, wherein the input signal comprises one or more of glucose or insulin levels in the subject; providing one or more “
i”
hidden layers,providing an output layer; providing at least one neuron “
Ylayer”
within each layer, where “
layer”
is the layer defined as “
input”
, “
hiddeni”
or “
output”
;providing one or more memory structures configured to;
a) store a recursive memory of input signals past, and b) allow for at least one time series prediction of a response;
wherein one or more memory structures are included in both the input and hidden layers; andforecasting one or more of;
elevated glucose levels or lack of optimal glycemic control. - View Dependent Claims (19, 20)
- elevated glucose levels or lack of optimal glycemic control, in a subject in need thereof, comprising;
Specification