PATENT CLAIM ANALYSIS

Application Number: 15756263
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-08
Patent Classification: ["382", "133000"]

Abstract:
A method and system for classification of endoscopic images is disclosed. An initial trained deep network classifier is used to classify endoscopic images and determine confidence scores for the endoscopic images. The confidence score for each endoscopic image classified by the initial trained deep network classifier is compared to a learned confidence threshold. For endoscopic images with confidence scores higher than the learned threshold value, the classification result from the initial trained deep network classifier is output. Endoscopic images with confidence scores lower than the learned confidence threshold are classified using a first specialized network classifier built on a feature space of the initial trained deep network classifier.

Claim (Index 15):
The method of  claim 14 , wherein classifying each of the confusion subset of the plurality of endoscopic images using one or more specialized network classifiers comprises:\n classifying of the endoscopic images in the confusion subset using a first specialized network classifier built on a feature space of the initial trained deep network classifier.

Metadata:
- Claim Count in Document: 75.0
- Percentile: 88.0
- Lexical Diversity: 2.11111
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15422483', '15420274', '09966408', '16075540', '14732002']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3644920995783243
- 35 USC 102 Novelty (BERT): 0.5052237287659281
- Combined Prediction Score: 0.3785652624970847
- Mean Citation Score: 224.312228
- Max Citation Score: 234.55705
- Similarity Product: 148.06343038960398

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