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 29):
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 clinical data objects stored in said memory, the clinical data objects containing clinical data of a plurality of patients from said database; \n one or more gene feature data objects stored in said memory, the gene feature data objects containing gene feature data of the plurality of patients from said database; \n one or more training data objects stored in said memory, the training data objects containing one or more training datasets generated based at least in part on the clinical data or the gene feature data; \n one or more initial predictive model data objects stored in said memory, the initial predictive model data objects containing parameters of one or more initial predictive models determined using one or more machine learning algorithms based at least in part on the one or more training datasets; \n one or more result data objects stored in said memory, the result data objects containing result data generated by applying the initial predictive models on the one or more training datasets; \n one or more ensemble data objects stored in said memory, the ensemble data objects containing ensemble data generated by performing an ensemble algorithm on the result data; and \n one or more final predictive model data objects stored in said memory, the final predictive model data objects containing parameters of one or more final predictive models determined based at least in part on the ensemble data; \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): 0.3890665874324867
- 35 USC 102 Novelty (BERT): 0.4921454199587524
- Combined Prediction Score: 0.3993744706851132
- Mean Citation Score: 190.618108
- Max Citation Score: 207.23244
- Similarity Product: 135.28483733403684

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