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METHOD FOR IDENTIFYING AND MONITORING ILLNESSES FROM GAS SAMPLES CAPTURED BY A DEVICE AND METHOD FOR TRAINING A NEURAL NETWORK TO IDENTIFY ILLNESSES FROM GAS SAMPLES CAPTURED BY A DEVICE
METHOD FOR IDENTIFYING AND MONITORING ILLNESSES FROM GAS SAMPLES CAPTURED BY A DEVICE AND METHOD FOR TRAINING A NEURAL NETWORK TO IDENTIFY ILLNESSES FROM GAS SAMPLES CAPTURED BY A DEVICE
The invention relates to a method for identifying and monitoring illnesses from gas samples captured by a device, including the steps of capturing at least one sample of gases present in the environment at an instant before capturing a gas sample from a user's breath, capturing the gas sample from a user's breath; capturing at least one sample of gases present in the environment at an instant after capturing the breath; generating a data array including data related to the gas samples captured; using the data array as input for at least one neural network trained to associate at least one illness with a gas signature, configuring the neural network to indicate whether the data array used as input generates a positive or negative output for the at least one illness.
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