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 14):
An ophthalmic image diagnostic method, comprising:\n displaying a test ophthalmic image on a display, the test ophthalmic image having at least one identified potentially abnormal region, each identified potentially abnormal region being associated with at least one abnormality type, and each abnormality type being further associated with at least one diagnosed ophthalmic sample; highlighting on the display any potentially abnormal region of the test ophthalmic image; and following a user-selection of a highlighted region of the displayed test ophthalmic image, displaying at least one diagnosed ophthalmic sample associated with the selected highlighted region.

Metadata:
- Claim Count in Document: 15.0
- Percentile: 90.0
- Lexical Diversity: 1.77358
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15810694', '15879486', '15429806', '15680584', '15799129']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2961301050831741
- 35 USC 102 Novelty (BERT): 0.5068779556427472
- Combined Prediction Score: 0.3172048901391314
- Mean Citation Score: 143.425428
- Max Citation Score: 147.84746
- Similarity Product: 74.99561689408543

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