PATENT CLAIM ANALYSIS

Application Number: 16115444
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-04
Patent Classification: ["702", "019000"]

Abstract:
The invention provides methods that use machine learning to discover within clinical data patterns that are predictive of disease. Clinical data from across a population is provided as input to a machine learning system. The autonomous machine learning system discovers associations in data from a plurality of data sources obtained from a population and correlates the associations to health status of patients in the population. The methods may further include providing patient data from an individual; and predicting, by the machine learning system, a health state for the individual when the patient data presents one or more of the discovered associations.

Claim (Index 7):
The method of  claim 6 , wherein the sample comprises nucleic acid from the individual and the assay includes sequencing the nucleic acid, wherein the clinical results include sequences or expression level, and further wherein providing the patient data includes obtaining clinical diagnostic codes from the individual.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 96.0
- Lexical Diversity: 1.77049
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14851530', '13294959', '13995284', '15977347', '15350915']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1740242006129281
- 35 USC 102 Novelty (BERT): 0.5044706956558354
- Combined Prediction Score: 0.2070688501172188
- Mean Citation Score: 158.020424
- Max Citation Score: 163.85414
- Similarity Product: 94.66440941917062

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

Dataset: test