PATENT CLAIM ANALYSIS

Application Number: 15971952
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2019-01
Patent Classification: ["706", "025000"]

Abstract:
Systems and methods are provided for performing predictive assignments pertaining to genetic information. One embodiment is a system that includes a genetic prediction server. The genetic prediction server includes an interface that acquires records that each indicate one or more genetic variants determined to exist within an individual, and a controller. The controller selects one or more machine learning models that utilize the genetic variants as input, and loads the machine learning models. For each individual in the records: the controller predictively assigns at least one characteristic to that individual by operating the machine learning models based on at least one genetic variant indicated in the records for that individual. The controller also generates a report indicating at least one predictively assigned characteristic for at least one individual, and transmits a command via the interface for presenting the report at a display.

Claim (Index 8):
A method comprising:\n acquiring records that each indicate one or more genetic variants determined to exist within an individual; selecting one or more machine learning models that utilize genetic variants as input; for each individual in the records, predictively assigning at least one characteristic to that individual by operating the one or more machine learning models, utilizing at least one genetic variant indicated in the records for that individual as input to the one or more machine learning models; analyzing input indicating accuracy of a predictively assigned characteristic; determining a score for a machine learning model based on the analyzed input and a cost function, wherein each of the one or more machine learning models comprises a multi-layer neural network, each layer comprising multiple nodes, wherein nodes in different layers are coupled via weighted connections, nodes in an input layer of the neural network each receive input indicating whether a different genetic variant exists within the individual, and nodes in an output layer of the neural network each provide output predicting whether a different characteristic is predicted for the individual; and revising the weighted connections based on the score.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 2.08219
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14739432', '15489564', '15404052', '14568456', '14465599']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3110274899413729
- 35 USC 102 Novelty (BERT): 0.4909199300078848
- Combined Prediction Score: 0.3290167339480241
- Mean Citation Score: 166.90926799999997
- Max Citation Score: 197.37247
- Similarity Product: 138.21386606234074

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

Dataset: test