PATENT CLAIM ANALYSIS

Application Number: 15860395
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-07
Patent Classification: ["382", "224000"]

Abstract:
A computer-implemented method for identifying character traits associated with a target subject includes acquiring image data of a target subject from an image data source, rendering a 3D image data set, comparing each of a plurality of regions of interest within the 3D image set to a historical image data set to identify active regions of interest, grouping subsets of the regions of interest into one or more convolutional feature layers, wherein each convolutional feature layer probabilistically maps to a pre-identified character trait, and applying a convolutional neural network model to the convolutional feature layers to identify a pattern of active regions of interest within each convolutional feature layer to predict whether a target subject possesses the pre-identified character trait.

Claim (Index 12):
The system of  claim 11 , wherein the computer executable instructions are further configured to cause the processor to:\n store the one or more convolutional neural networks in the data store; and for each pre-defined character trait, extrapolate from the one or more convolutional neural networks, one or more regions of interest correlated to the pre-defined character trait.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 86.0
- Lexical Diversity: 2.1
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15172826', '14835736', '15452076', '15194541', '15225597']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3567236858691179
- 35 USC 102 Novelty (BERT): 0.4929764239578113
- Combined Prediction Score: 0.3703489596779872
- Mean Citation Score: 202.509954
- Max Citation Score: 207.36055
- Similarity Product: 141.65971792970598

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test