PATENT CLAIM ANALYSIS

Application Number: 16162695
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-10
Patent Classification: ["703", "011000"]

Abstract:
A system is provided for generating a classifier for classifying electromagnetic data (e.g., ECG) derived from an electromagnetic source (e.g., heart). The system accesses a computational model of the electromagnetic source. The computational model models the electromagnetic output of the electromagnetic source over time based on a source configuration (e.g., rotor location) of the electromagnetic source. The system generates, for each different source configuration (e.g., different rotor locations), a modeled electromagnetic output (e.g., ECG) of the electromagnetic source for that source configuration. For each modeled electromagnetic output, the system derives the electromagnetic data for the modeled electromagnetic output and generates a label (e.g., rotor location) for the derived electromagnetic data from the source configuration for the modeled electromagnetic data. The system trains a classifier with the derived electromagnetic data and the labels as training data. The classifier can then be used to classify the electromagnetic output collected from patients.

Claim (Index 11):
The method of  claim 1  wherein the classifier is a recurrent neural network, an autoencoder, or a restricted Boltzmann machine.

Metadata:
- Claim Count in Document: 63.0
- Percentile: 97.0
- Lexical Diversity: 2.95
- Patent Class: 703.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15389245', '15261013', '14199495', '14578205', '15320644']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2399500139185565
- 35 USC 102 Novelty (BERT): 0.5056243392398166
- Combined Prediction Score: 0.2665174464506826
- Mean Citation Score: 115.818811
- Max Citation Score: 136.49383999999998
- Similarity Product: 72.88176058886526

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

Dataset: test