PATENT CLAIM ANALYSIS

Application Number: 15909658
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["382", "128000"]

Abstract:
An ophthalmic image diagnostic tool and method submits a test image to a neural network trained to identify abnormal regions of an ophthalmic image, to distinguish between multiple types of abnormalities, and to associate an abnormality type with each identified potentially abnormal region. Each potentially abnormal region in the test image is highlighted, and in response to a user-selection of a highlighted region, a previously diagnosed sample (e.g., from a library of samples) of the abnormality type associated with the selected highlighted region is displayed.

Claim (Index 13):
The method of  claim 1 , wherein the test ophthalmic image is an en face ophthalmic image.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 90.0
- Lexical Diversity: 1.77358
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15810694', '15879486', '15429806', '15680584', '15799129']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3235072221733891
- 35 USC 102 Novelty (BERT): 0.5005869423912344
- Combined Prediction Score: 0.3412151941951736
- Mean Citation Score: 143.425428
- Max Citation Score: 147.84746
- Similarity Product: 82.29080856081843

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