PATENT CLAIM ANALYSIS

Application Number: 15865581
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-08
Patent Classification: ["382", "128000"]

Abstract:
Systems and methods are provided for performing medical imaging analysis. Input medical imaging data is received for performing a particular one of a plurality of medical imaging analyses. An output that provides a result of the particular medical imaging analysis on the input medical imaging data is generated using a neural network trained to perform the plurality of medical imaging analyses. The neural network is trained by learning one or more weights associated with the particular medical imaging analysis using one or more weights associated with a different one of the plurality of medical imaging analyses. The generated output is outputted for performing the particular medical imaging analysis.

Claim (Index 5):
The method of  claim 4 , wherein the set of weights for each node comprises:\n a hypernet weight comprising the weight at the top level of the hierarchical relationship; one or more ultranet weights each associated with a modality and one or more ultranet weights each associated with an anatomy; one or more supernet weights each associated with a modality and an anatomy; and a plurality of target network weights comprising the weights at the bottom level of the hierarchical relationship.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 86.0
- Lexical Diversity: 2.45652
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15382414', '15618384', '15689411', '15689046', '15397638']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3273836067259829
- 35 USC 102 Novelty (BERT): 0.4994974270133352
- Combined Prediction Score: 0.3445949887547181
- Mean Citation Score: 219.622492
- Max Citation Score: 229.97845
- Similarity Product: 150.80049494613706

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