PATENT CLAIM ANALYSIS

Application Number: 16200089
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["600", "518000"]

Abstract:
A system and method for machine-learning based atrial fibrillation detection are provided. A database is maintained that is operable to maintain a plurality of ECG features and annotated patterns of the features. At least one server is configured to: train a classifier based on the annotated patterns in the database; receive a representation of an ECG signal recorded by an ambulatory monitor recorder during a plurality of temporal windows; detect a plurality of the ECG features in at least some of the portions of the representation falling within each of the temporal windows; use the trained classifier to identify patterns of the ECG features within one or more of the portions of the ECG signal; for each of the portions, calculate a score indicative of whether the portion of the representation within that ECG signal is associated the patient experiencing atrial fibrillation; and take an action based on the score.

Claim (Index 11):
A method for machine-learning-based atrial fibrillation detection with the aid of a digital computer, comprising:\n maintaining in a database a plurality of electrocardiography (ECG) features and annotated patterns of the features, at least some of the patterns associated with atrial fibrillation; training by an at least one server connected to the database a classifier based on the annotated patterns in the database; receiving by the at least one server a representation of an ECG signal recorded by an ambulatory monitor recorder during a plurality of temporal windows; detecting by the at least one server a plurality of the ECG features in at least some of the portions of the representation falling within each of the temporal windows; using by the at least one server the trained classifier to identify patterns of the ECG features within one or more of the portions of the ECG signal; for each of the portions, calculating by the at least one server a score indicative of whether the portion of the representation within that ECG signal is associated the patient experiencing atrial fibrillation; and taking by the at least one server an action based on the score.

Metadata:
- Claim Count in Document: 19.0
- Percentile: 98.0
- Lexical Diversity: 2.16216
- Patent Class: 600.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14217402', '15162489', '15682242', '14656615', '16105603']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5568331524484365
- 35 USC 102 Novelty (BERT): 0.520773687041468
- Combined Prediction Score: 0.5532272059077397
- Mean Citation Score: 346.168806
- Max Citation Score: 359.79858
- Similarity Product: 288.30374600297216

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

Dataset: test