PATENT CLAIM ANALYSIS

Application Number: 15910379
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["715", "211000"]

Abstract:
There is provided a method of creating a cohort clinical pathway graph based on knowledge-driven manual user input and automated data-driven mining comprising: receiving via a graphical user interface (GUI), manual selections including: knowledge-driven variable(s) denoting clinically significant values representing elements of a clinical decision making process, and an anchoring location of each knowledge-driven node denoting a respective knowledge-drive variable within a directed acyclic graph (DAG), computing individual clinical pathways for each of the sampled population of patients by automatically computing data-driven nodes denoting the data-driven discovery of event types relative to the manual selections, and aggregating the individual clinical pathways to compute a cohort clinical pathway DAG, wherein the cohort clinical pathway DAG includes nodes comprising the knowledge-driven nodes, the data-driven nodes, and links connecting the nodes, each link denoting an automatically discovered sequence between two respective nodes, and presenting the cohort clinical pathway DAG within the GUI.

Claim (Index 14):
The method according to  claim 1 , further comprising receiving, via the GUI, a manual designation indicative of automated data-driven discovery of events at least one of: before, after, and in-between knowledge-driven nodes of the at least one knowledge-driven variables, wherein the automatically computing the data-driven discovery of events is performed according to the manual designation.

Metadata:
- Claim Count in Document: 45.0
- Percentile: 90.0
- Lexical Diversity: 2.0
- Patent Class: 715.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13069623', '13837370', '14195559', '10850232', '14324396']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2973785177166195
- 35 USC 102 Novelty (BERT): 0.495583662223707
- Combined Prediction Score: 0.3171990321673282
- Mean Citation Score: 169.474402
- Max Citation Score: 195.95576
- Similarity Product: 115.5819137673044

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