PATENT CLAIM ANALYSIS

Application Number: 16091973
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-06
Patent Classification: ["702", "019000"]

Abstract:
The present disclosure is directed towards methods for calculating disease progression rates and sojourn times of solid tumors from metabolic markers and using this calculation to optimize patient-specific diagnosis, scheduling of screening procedures, and dosage or frequency of treatment.

Claim (Index 1):
A method for optimizing diagnostics and therapeutic procedures for solid tumors in a human patient by measuring metabolic markers during exercise, the method comprising the steps of:\n providing the patient with an exercising equipment; allowing the patient to exercise on the exercising equipment for a period of time; adjusting an exercise level of the patient to the patient's age and heart rate; measuring the level of at least one metabolic marker in a patient during exercise;\n calculating disease progression rates and sojourn times based on a functional relation between the at least one metabolic marker and disease progression rates and sojourn time; and \n predicting at least one incident selected from the group consisting of: diagnosis, timing of screening procedures, a type of treatment, a dosage of treatment, a timing of treatment, and a frequency of treatment.

Metadata:
- Claim Count in Document: 18.0
- Percentile: 97.0
- Lexical Diversity: 1.13514
- Patent Class: 702.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15673191', '14078058', '16133322', '14048880', '14729987']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.1753049756836575
- 35 USC 102 Novelty (BERT): 0.4804498887696259
- Combined Prediction Score: 0.2058194669922544
- Mean Citation Score: 112.7584756
- Max Citation Score: 116.070076
- Similarity Product: 70.78360504099489

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test