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 9):
The method of  claim 6 , the method further comprising (c) identifying, by the computer, characteristic event features indicative of the status of the condition, thereby providing the status of the condition of the biological data sample and diagnosing the status of the condition in the subject.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 90.0
- Lexical Diversity: 1.34375
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15445913', '15532844', '13125054', '11928901', '16085077']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3444067879845886
- 35 USC 102 Novelty (BERT): 0.5639020095736702
- Combined Prediction Score: 0.3663563101434968
- Mean Citation Score: 218.638974
- Max Citation Score: 426.39444
- Similarity Product: 285.81763488889214

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