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 30):
A non-transitory computer-readable medium for storing data for access by an application program being executed on a data processing system, comprising:\n a data structure stored in said memory, said data structure including information, resident in a database used by said application program and including:\n one or more training data objects stored in said memory, the training data objects containing a training dataset from said database, the training dataset including a plurality of sub-datasets; \n one or more first predictive model data objects stored in said memory, the first predictive model data objects containing parameter data of a first predictive model determined using one or more machine learning algorithms based at least in part on one or more first training sub-datasets from the plurality of sub-datasets; \n one or more final predictive model data objects stored in said memory, the final predictive model data objects containing parameter data of a final predictive model determined based at least in part on performance evaluation of the first predictive model; \n wherein the final predictive model data objects are used by said application program for predicting regimen-related outcomes.

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): 0.3916927468974043
- 35 USC 102 Novelty (BERT): 0.4810185558394991
- Combined Prediction Score: 0.4006253277916138
- Mean Citation Score: 190.618108
- Max Citation Score: 207.23244
- Similarity Product: 153.32155985695127

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

Dataset: test