PATENT CLAIM ANALYSIS

Application Number: 16376366
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2019-08
Patent Classification: ["382", "131000"]

Abstract:
A computer implemented method for assessing an arterio-venous malformation (AVM) may include, for example, receiving a patient-specific model of a portion of an anatomy of a patient; using a computer processor to analyze the patient-specific model for identifying one or more blood vessels associated with the AVM, in the patient-specific model; and estimating a risk of an undesirable outcome caused by the AVM, by performing computer simulations of blood flow through the one or more blood vessels associated with the AVM in the patient-specific model.

Claim (Index 21):
A computer implemented method for assessing an arterio-venous malformation (AVM), the method comprising:\n receiving image data of at least a portion of a vascular system of a patient, including one or more blood vessels having at least one vessel wall associated with the AVM; generating a patient-specific three-dimensional anatomic model of the portion of the vascular system of the patient, using the received image data; identifying, using a computer processor, a blood vessel of the patient-specific three-dimensional anatomic model; determining a vessel wall property of the identified blood vessel; performing a blood flow simulation through the identified blood vessel, based on the determined vessel wall property; and generating a treatment recommendation for treating AVM of the identified blood vessel based on the performed blood flow simulation.

Metadata:
- Claim Count in Document: 59.0
- Percentile: 100.0
- Lexical Diversity: 1.84314
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15977140', '14842960', '15807394', '14848021', '15210712']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3298884202868373
- 35 USC 102 Novelty (BERT): 0.5902930990306896
- Combined Prediction Score: 0.3559288881612225
- Mean Citation Score: 369.89375000000007
- Max Citation Score: 483.85153
- Similarity Product: 468.1314749160421

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