PATENT CLAIM ANALYSIS

Application Number: 15973498
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-11
Patent Classification: ["704", "243000"]

Abstract:
A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

Claim (Index 9):
The computer-implemented method of  claim 8 , wherein the medical condition is a concussion or Alzheimer's disease.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 2.87037
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15973504', '14640955', '15850106', '13959171', '15055417']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2357675359525667
- 35 USC 102 Novelty (BERT): 0.5250361704576346
- Combined Prediction Score: 0.2646943994030735
- Mean Citation Score: 196.13005
- Max Citation Score: 273.94684
- Similarity Product: 156.08031702672002

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