PATENT CLAIM ANALYSIS

Application Number: 16124108
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["702", "019000"]

Abstract:
Embodiments of a method and/or system (e.g., for nasal-related characterization) can include determining a microorganism dataset associated with a set of subjects; and/or performing a characterization process based on the microorganism dataset, where performing the characterization process can additionally or alternatively include performing a nasal-related characterization process, and/or determining one or more therapies, such as for one or more nasal-related conditions.

Claim (Index 5):
The method of  claim 4 , wherein the nasal-related characterization model comprises a calendar season characterization machine learning model, wherein generating the nasal-related characterization model comprises training the calendar season characterization machine learning model based on the set of microbiome composition features and calendar seasons associated with the samples collected from the nose sites of the set of subjects, and wherein determining the calendar season parameter comprises determining the calendar season parameter based on the calendar season characterization machine learning model and the user sample collected at the nose site of the user.

Metadata:
- Claim Count in Document: 56.0
- Percentile: 97.0
- Lexical Diversity: 1.76923
- Patent Class: 702.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15997654', '15844360', '15452529', '15845190', '15606943']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1923745284259726
- 35 USC 102 Novelty (BERT): 0.5217951138322449
- Combined Prediction Score: 0.2253165869665998
- Mean Citation Score: 252.81871400000009
- Max Citation Score: 299.00024
- Similarity Product: 200.9075743885136

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

Dataset: test