PATENT CLAIM ANALYSIS

Application Number: 15939621
Application Type: Utility
Filing Date: 2018-03
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 14):
The method of  claim 1 , wherein generating one or more training datasets and one or more testing datasets based at least in part on clinical data or gene feature data of a plurality of patients includes:\n generating one or more clinical predictor datasets by generating binary predictor data based at least in part on the clinical data.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 90.0
- Lexical Diversity: 1.51852
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14458575', '10955591', '11371511', '13246596', '12349628']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4194614998477824
- 35 USC 102 Novelty (BERT): 0.4870084625254705
- Combined Prediction Score: 0.4262161961155513
- Mean Citation Score: 190.618108
- Max Citation Score: 207.23244
- Similarity Product: 147.33138795118333

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