Difference between revisions of "Ovarian Cancer Detection by an Electronic Nose"
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|title=Ovarian Cancer Detection by an Electronic Nose | |title=Ovarian Cancer Detection by an Electronic Nose | ||
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|coordinator=AndreaBonarini; MatteoMatteucci | |coordinator=AndreaBonarini; MatteoMatteucci | ||
|tutor=RossellaBlatt; | |tutor=RossellaBlatt; | ||
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|type=Course | |type=Course | ||
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| + | === Short description === | ||
| + | |||
| + | The project aims at evaluating the possibility of diagnosing ovarian cancer using an electronic nose, already used with success in the lung cancer detection ( [[Lung Cancer Detection by an Electronic Nose]] ). | ||
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| + | |||
| + | === Laboratory work and risk analysis === | ||
| + | |||
| + | Laboratory work for this project will be mainly performed at the Istituto Nazionale dei Tumori di Milano, where the acquisistion of subjects' breath, both sick and healthy will be done. | ||
| + | For this kind of work, there are not potential risks. | ||
| + | |||
| + | === Project description === | ||
| + | |||
The electronic nose is an instrument able to detect and recognize odors, that is the volatile substances in the atmosphere or emitted by the analyzed substance. This device can react to a gas substance by providing signals that can be analyzed to classify the input. It is composed of a sensor array (MOS sensors, in our case) and a pattern classification process based on machine learning techniques. Each sensor reacts in a different way to the analyzed substance, providing multidimensional data that can be considered as a unique olfactory blueprint of the analyzed substance. In our work, we used an array composed of six Metal Oxide Semiconductor (MOS) sensors. | The electronic nose is an instrument able to detect and recognize odors, that is the volatile substances in the atmosphere or emitted by the analyzed substance. This device can react to a gas substance by providing signals that can be analyzed to classify the input. It is composed of a sensor array (MOS sensors, in our case) and a pattern classification process based on machine learning techniques. Each sensor reacts in a different way to the analyzed substance, providing multidimensional data that can be considered as a unique olfactory blueprint of the analyzed substance. In our work, we used an array composed of six Metal Oxide Semiconductor (MOS) sensors. | ||
| − | In this project, we have been using an electronic nose based on an array of six MOS sensors, to recognize the presence of | + | In this project, we have been using an electronic nose based on an array of six MOS sensors, to recognize the presence of ovarian cancer in breaths' subjects, diagnosing the disease with a non invasive and low cost method. |
| + | |||
| + | === Progress === | ||
| + | |||
| + | At this moment we are still taking samples. | ||
Revision as of 14:55, 14 October 2010
Ovarian Cancer Detection by an Electronic Nose
| |
| Coordinator: | AndreaBonarini (andrea.bonarini@polimi.it), MatteoMatteucci (matteo.matteucci@polimi.it) |
| Tutor: | RossellaBlatt (blatt@elet.polimi.it) |
| Collaborator: | |
| Students: | AlessandroMariaMauri (), NiccoloMoretti () |
| Research Topic: | Early cancer detection |
| Start: | 2009/10/01 |
| Status: | Active |
| Level: | Ms |
| Type: | Course |
Short description
The project aims at evaluating the possibility of diagnosing ovarian cancer using an electronic nose, already used with success in the lung cancer detection ( Lung Cancer Detection by an Electronic Nose ).
Laboratory work and risk analysis
Laboratory work for this project will be mainly performed at the Istituto Nazionale dei Tumori di Milano, where the acquisistion of subjects' breath, both sick and healthy will be done. For this kind of work, there are not potential risks.
Project description
The electronic nose is an instrument able to detect and recognize odors, that is the volatile substances in the atmosphere or emitted by the analyzed substance. This device can react to a gas substance by providing signals that can be analyzed to classify the input. It is composed of a sensor array (MOS sensors, in our case) and a pattern classification process based on machine learning techniques. Each sensor reacts in a different way to the analyzed substance, providing multidimensional data that can be considered as a unique olfactory blueprint of the analyzed substance. In our work, we used an array composed of six Metal Oxide Semiconductor (MOS) sensors. In this project, we have been using an electronic nose based on an array of six MOS sensors, to recognize the presence of ovarian cancer in breaths' subjects, diagnosing the disease with a non invasive and low cost method.
Progress
At this moment we are still taking samples.
