PATENT CLAIM ANALYSIS

Application Number: 15912511
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-08
Patent Classification: ["706", "020000"]

Abstract:
The present disclosure provides methods for applying artificial neural networks to flow cytometry data generated from biological samples to diagnose and characterize cancer in a subject. The disclosure also provides methods of training, testing, and validating artificial neural networks.

Claim (Index 8):
The method of  claim 6 , wherein the artificial neural network is one of at least three artificial neural networks that are used by a master network where the at least three artificial networks vary in at least one of number of network layers, number of neurons used, training function, method of output error calculation, weight and bias updating method, number of inputs, type of inputs, and combinations thereof.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 90.0
- Lexical Diversity: 1.34375
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15445913', '15532844', '13125054', '11928901', '16085077']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3705641480210897
- 35 USC 102 Novelty (BERT): 0.5683496802454523
- Combined Prediction Score: 0.390342701243526
- Mean Citation Score: 218.638974
- Max Citation Score: 426.39444
- Similarity Product: 308.2714086639976

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test