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 26):
A processor-implemented system for building a predictive model for predicting regimen-related outcomes, the system comprising:\n one or more processors configured to:\n divide a training dataset into a plurality of sub-datasets; \n select one or more first training sub-datasets from the plurality of sub-datasets; \n determine a first predictive model using one or more machine learning algorithms based at least in part on the one or more first training sub-datasets; \n evaluate the performance of the first predictive model using the plurality of sub-datasets excluding the one or more first training sub-datasets; and \n determine a final predictive model based at least in part on the performance evaluation of the first predictive model; \n one or more non-transitory machine-readable storage media for storing a computer database having a database schema that includes and interrelates training data fields, first predictive model data fields, and final predictive model data fields, the training data fields storing the training dataset, the first predictive model data fields storing parameter data of the first predictive model, and the final predictive model data fields storing parameter data of the final predictive model.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 90.0
- Lexical Diversity: 1.51852
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14458575', '10955591', '11371511', '13246596', '12349628']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3926315439376633
- 35 USC 102 Novelty (BERT): 0.4770514647592822
- Combined Prediction Score: 0.4010735360198252
- Mean Citation Score: 190.618108
- Max Citation Score: 207.23244
- Similarity Product: 159.75873886873484

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