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 17):
A processor-implemented method for determining a treatment regimen for a patient, the method comprising:\n generating, using the one or more data processors, one or more training datasets and one or more testing datasets based at least in part on sample clinical data or sample gene feature data; determining, using one or more data processors, one or more initial predictive models using one or more machine learning algorithms based at least in part on the one or more training datasets; applying, using the one or more data processors, the one or more initial predictive models on the one or more training datasets to generate result data; performing, using the one or more data processors, an ensemble algorithm on the result data to generate ensemble data; determining, using the one or more data processors, one or more final predictive models based at least in part on the ensemble data; evaluating, using the one or more data processors, performance of the one or more final predictive models based at least in part on the one or more test datasets; predicting, using the one or more data processors, regimen-related outcomes using the one or more final predictive models based at least in part on clinical data or gene feature data of a patient; assessing patient preferences of the patient to generate patient preference data; and determining a treatment regimen for the patient based on the regimen-related outcomes and the patient preference data.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 91.0
- Lexical Diversity: 1.51852
- Patent Class: 706.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14458575', '10955591', '11371511', '15373177', '13246596']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3680735052974401
- 35 USC 102 Novelty (BERT): 0.4871265045402095
- Combined Prediction Score: 0.379978805221717
- Mean Citation Score: 189.766514
- Max Citation Score: 211.95692000000005
- Similarity Product: 148.55846137395622

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