System and method for analyzing spectral data using artificial intelligence
AssigneeVionix Biosciences Inc.
InventorsVivek Wadhwa, Purshotam Rajani
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Abstract
A system provides for an ability to automatically identify one or more chemical components of a sample, based on analysis of spectral data by at least one artificial intelligence module. The artificial intelligence module is able to be trained on a plurality of spectral data samples having known concentrations of individual chemicals and elements. The system is further operable to calculate the correlations between spectral data samples of varying concentrations and predict the concentration of the one or more chemical components of the sample.
Claims20
An artificial intelligence (AI)-based system for automatically identifying molecules in a sample, comprising:
- one or more devices, comprising a processor and a memory, configured to receive training data from one or more spectrometers or chemical analysis devices;
- and
- an AI module on the one or more devices configured to automatically develop characteristic profiles for a plurality of training samples;
- wherein the training data comprises a plurality of measured spectral graphs corresponding with the training samples of known elements, known compounds, and/or known mixtures;
- wherein the AI module calculates a normalized spectral graph for each of the measured spectral graphs corresponding with the training samples;
- wherein the one or more devices receive experimental data from a testing spectrometer;
- wherein the experimental data comprises a plurality of unknown elements, unknown compounds and/or unknown mixtures;
- and
- wherein the AI module is operable to utilize the normalized spectral graphs to determine the plurality of unknown elements, unknown compounds and/or unknown mixtures in the experimental data.
An artificial intelligence (AI)-based method for automatically identifying molecules in a sample, comprising:
- receiving training data from one or more spectrometers or chemical analysis devices via one or more devices comprising a processor and a memory;
- automatically developing characteristic profiles for a plurality of training samples;
- wherein the training data comprises a plurality of measured spectral graphs corresponding with the training samples of known elements, known compounds and/or known mixtures;
- calculating a normalized spectral graph for each of the measured spectral graphs corresponding with the training samples;
- receiving experimental data comprising a plurality of unknown elements, unknown compounds and/or unknown mixtures from a testing spectrometer;
- and
- determining the plurality of unknown elements, unknown compounds and/or unknown mixtures in the experimental data via the normalized spectral graphs.
An artificial intelligence (AI)-based system for automatically identifying molecules in a sample, comprising:
- one or more cloud servers configured to receive training data from one or more spectrometers or chemical analysis devices;
- and
- an AI module on the one or more cloud servers configured to automatically develop characteristic profiles for a plurality of training samples;
- wherein the training data comprises a plurality of measured spectral graphs corresponding with the training samples of known elements, known compounds, and/or known mixtures;
- wherein the AI module calculates a normalized spectral graph for each of the measured spectral graphs corresponding with the training samples;
- wherein the one or more cloud servers receive experimental data comprising a plurality of unknown elements, unknown compounds and/or unknown mixtures testing spectrometer;
- wherein the AI module is operable to utilize the normalized spectral graphs to determine the plurality of unknown elements, unknown compounds and/or unknown mixtures in the experimental data;
- and
- wherein the AI module automatically generates a report with indications of present identified molecules based on comparison of the experimental data to the characteristic profiles.
Dependencies are inferred from the claim text.