Methods and systems for classifying biological samples, including optimization of analyses and use of correlation

A method for classifying a biological sample, the method comprising:

• receiving an image of a biological sample;
• applying, via a processor, one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes selecting a minimum training set size;
• generating, via the processor, a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• and
• transmitting the classification of the biological sample to be presented via a presentation medium.

A method for classifying a biological sample, the method comprising:

• receiving an image of a biological sample;
• applying, via processor, one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes selecting a cohort;
• generating, via a processor, a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• and
• transmitting the classification of the biological sample to be presented via a presentation medium.

A method for establishing platform independence of spectral histopathology (SHP) reflectance infrared micro-spectral images, comprising:

• receiving a spectral image from a first image generating machine at a first time;
• analyzing, via a processor, the spectral image to identify signature information of the first image generating machine based on the spectral image;
• and
• storing the signature information associated with the first image generating machine in a master reference database.

A system for classifying a biological sample, the system comprising:

• a memory in communication with a processor, wherein the memory and the processor are cooperatively configured to:
• receive an image of a biological sample;
• apply one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes optimizing a threshold of data;
• generate a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• and
• transmit the classification of the biological sample to be presented via a presentation medium.

A system for classifying a biological sample, the system comprising:

• a memory in communication with a processor, wherein the memory and the processor are cooperatively configured to:
• receive an image of a biological sample;
• apply one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes selecting a minimum training set size;
• generate a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• and
• transmit the classification of the biological sample to be presented via a presentation medium.

A system for establishing platform independence of spectral histopathology (SHP) reflectance infrared micro-spectral images, the system comprising:

• a memory in communication with a processor, wherein the memory and the processor are cooperatively configured to:
• receive a spectral image from a first image generating machine at a first time;
• analyze the spectral image to identify signature information of the first image generating machine based on the spectral image;
• and
• store the signature information associated with the first image generating machine in a master reference database.

A system for classifying a biological sample, the system comprising:

• a receiving module for receiving an image of a biological sample;
• a selecting module for applying one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes optimizing a threshold of data;
• a generating module for generating a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• a transmitting module for transmitting the classification of the biological sample to be presented via a presentation medium.

A system for classifying a biological sample, the system comprising:

• a receiving module for receiving an image of a biological sample;
• a selecting module for applying one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes selecting a minimum training set size;
• a generating module for generating a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• a transmitting module for transmitting the classification of the biological sample to be presented via a presentation medium.

A system for classifying a biological sample, the system comprising:

• a receiving module for receiving an image of a biological sample;
• a selecting module for applying one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes selecting a cohort;
• a generating module for generating a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• a transmitting module for transmitting the classification of the biological sample to be presented via a presentation medium.

A computer program product, comprising:

• a computer-readable medium including:
• at least a first instruction for causing a computer to receive an image of a biological sample;
• at least a second instruction for causing the computer to apply one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes optimizing a threshold of data;
• at least a third instruction for causing the computer to generate a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• and
• at least a fourth instruction for causing the computer to transmit the classification of the biological sample to be presented via a presentation medium.

A computer program product, comprising:

• a computer-readable medium including:
• at least a first instruction for causing a computer to receive an image of a biological sample;
• at least a second instruction for causing the computer to apply one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes selecting a minimum training set size;
• at least a third instruction for causing the computer to generate a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• and
• at least a fourth instruction for causing the computer to transmit the classification of the biological sample to be presented via a presentation medium.

A computer program product, comprising:

• a computer-readable medium including:
• at least a first instruction for causing a computer to receive an image of a biological sample;
• at least a second instruction for causing the computer to apply one or more algorithms based on information in a data repository to the image, wherein applying one or more algorithms includes selecting a cohort;
• at least a third instruction for causing the computer to generate a classification of the biological sample based on the outcome of the one or more algorithms applied to the image;
• and
• at least a fourth instruction for causing the computer to transmit the classification of the biological sample to be presented via a presentation medium.

A computer program product, comprising:

• a computer-readable medium including:
• at least a first instruction for causing a computer to receive a spectral image from a first image generating machine at a first time;
• at least a second instruction for causing the computer to analyze the spectral image to identify signature information of the first image generating machine based on the spectral image;
• and
• at least a third instruction for causing the computer to store the signature information associated with the first image generating machine in a master reference database.