PATENT CLAIM ANALYSIS

Application Number: 15953544
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-08
Patent Classification: ["706", "012000"]

Abstract:
Systems and methods are provided for predicting treatment-regimen-related outcomes (e.g., risks of regimen-related toxicities). A predictive model is determined for predicting treatment-regimen-related outcomes and applied to a plurality of datasets. An ensemble algorithm is applied on result data generated from the application of the predictive model. Treatment-regimen-related outcomes are predicted using the predictive model. A combination of machine learning prediction and patient preference assessment is provided for enabling informed consent and precise treatment decisions.

Claim (Index 8):
The method of  claim 7 , wherein performing recursive partitioning for filtering the plurality of SNPs includes:\n dividing a gene feature dataset related to the plurality of SNPs into a plurality of sub-datasets; selecting one or more first sub-datasets from the plurality of sub-datasets; developing a first recursive partitioning model based at least in part on the one or more first sub-datasets; and determining one or more first predictive SNPs based at least in part on the first recursive partitioning model, wherein the one or more first predictive SNPs are included into the one or more filtered SNPs.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 91.0
- Lexical Diversity: 1.51852
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14458575', '10955591', '11371511', '15373177', '13246596']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3980907500528506
- 35 USC 102 Novelty (BERT): 0.4810992713073415
- Combined Prediction Score: 0.4063916021782997
- Mean Citation Score: 189.766514
- Max Citation Score: 211.95692000000005
- Similarity Product: 162.76858945337298

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

Dataset: test