PATENT CLAIM ANALYSIS

Application Number: 16155805
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-04
Patent Classification: ["705", "002000"]

Abstract:
A system and method are disclosed for enhancing the efficiency and accuracy of analysis and interpretation of medical diagnostic laboratory test data for real-time clinical decision support, utilizing artificial intelligence techniques to automatically improve analytical performance and enhance provider and patient communications.

Claim (Index 15):
A tangible, non-transitory, machine-readable medium storing instructions that when executed by one or more processors effectuate operations comprising:\n receiving laboratory test results for one or more diagnostic laboratory tests performed on a patient as ordered by a clinician; receiving other health information for said patient; storing said laboratory test results and said other health information for said patient in a secure data storage system; comparing said laboratory test results for said patient with reference information to create one or more initial diagnostic interpretations for said patient; comparing said other health information for said patient with other reference information to modify said one or more initial diagnostic interpretations for said patient; analyzing said one or more modified diagnostic interpretations with one or more machine learning algorithms to produce one or more medical diagnoses and one or more clinical recommendations for said patient; storing said one or more modified diagnostic interpretations, said one or more medical diagnoses and said one or more clinical recommendations for said patient in said secure data storage system; producing a diagnostic report for said clinician comprising said one or more modified diagnostic interpretations, said one or more medical diagnoses and said one or more clinical recommendations for said patient; producing a diagnostic report for said patient comprising a subset of the information in said diagnostic report for said clinician; and receiving feedback from said clinician for at least one of said one or more diagnostic interpretations and at least one of said one or more medical diagnoses for said patient, wherein said machine learning algorithm processes said feedback to increase accuracy of medical diagnoses and clinical recommendations.

Metadata:
- Claim Count in Document: 6.0
- Percentile: 97.0
- Lexical Diversity: 1.15789
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['10605125', '13294959', '11444081', '11031298', '15179434']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1018264060594152
- 35 USC 102 Novelty (BERT): 0.4846007873737647
- Combined Prediction Score: 0.1401038441908502
- Mean Citation Score: 186.77465
- Max Citation Score: 200.8563
- Similarity Product: 141.17135642454028

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