PATENT CLAIM ANALYSIS

Application Number: 16200093
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["382", "128000"]

Abstract:
Techniques for automating the generation and analysis of fundus drawings are described. Captured images undergo image processing to extract information about image features. Fundus images are generated and recommended labels for the fundus drawing are generated. Fundus drawings can be analyzed and undergo textual processing to extract existing labels. Machine learning models and co-occurrence analysis can be applied to collections of fundus images and drawings to gather information about commonly associated labels, label locations, and user information. The most frequently used labels associated with the image can be identified to improve recommendations and personalize labels.

Claim (Index 35):
The system of  claim 30 , wherein identifying the one or more image features comprises using an image segmentation technique.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 98.0
- Lexical Diversity: 1.87273
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15374027', '11954484', '13971092', '15235050', '14602524']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3234700475857006
- 35 USC 102 Novelty (BERT): 0.5110916781932341
- Combined Prediction Score: 0.3422322106464539
- Mean Citation Score: 164.646338
- Max Citation Score: 263.71188
- Similarity Product: 171.87310919895177

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