Detecting Disease in Radiographs with Intuitive Confidence
This paper argues in favor of a specific type of confidence for use in computer-aided diagnosis and disease classification, namely, sine/cosine values of angles represented by points on the unit circle. The paper shows how this confidence is motivated by Chinese medicine and how sine/cosine values a...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/946793 |
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| _version_ | 1832567143130988544 |
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| author | Stefan Jaeger |
| author_facet | Stefan Jaeger |
| author_sort | Stefan Jaeger |
| collection | DOAJ |
| description | This paper argues in favor of a specific type of confidence for use in computer-aided diagnosis and disease classification, namely, sine/cosine values of angles represented by points on the unit circle. The paper shows how this confidence is motivated by Chinese medicine and how sine/cosine values are directly related with the two forces Yin and Yang. The angle for which sine and cosine are equal (45°) represents the state of equilibrium between Yin and Yang, which is a state of nonduality that indicates neither normality nor abnormality in terms of disease classification. The paper claims that the proposed confidence is intuitive and can be readily understood by physicians. The paper underpins this thesis with theoretical results in neural signal processing, stating that a sine/cosine relationship between the actual input signal and the perceived (learned) input is key to neural learning processes. As a practical example, the paper shows how to use the proposed confidence values to highlight manifestations of tuberculosis in frontal chest X-rays. |
| format | Article |
| id | doaj-art-06ab8f78caec41178cdf51b040ac9fbf |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-06ab8f78caec41178cdf51b040ac9fbf2025-02-03T01:02:16ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/946793946793Detecting Disease in Radiographs with Intuitive ConfidenceStefan Jaeger0U.S. National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USAThis paper argues in favor of a specific type of confidence for use in computer-aided diagnosis and disease classification, namely, sine/cosine values of angles represented by points on the unit circle. The paper shows how this confidence is motivated by Chinese medicine and how sine/cosine values are directly related with the two forces Yin and Yang. The angle for which sine and cosine are equal (45°) represents the state of equilibrium between Yin and Yang, which is a state of nonduality that indicates neither normality nor abnormality in terms of disease classification. The paper claims that the proposed confidence is intuitive and can be readily understood by physicians. The paper underpins this thesis with theoretical results in neural signal processing, stating that a sine/cosine relationship between the actual input signal and the perceived (learned) input is key to neural learning processes. As a practical example, the paper shows how to use the proposed confidence values to highlight manifestations of tuberculosis in frontal chest X-rays.http://dx.doi.org/10.1155/2015/946793 |
| spellingShingle | Stefan Jaeger Detecting Disease in Radiographs with Intuitive Confidence The Scientific World Journal |
| title | Detecting Disease in Radiographs with Intuitive Confidence |
| title_full | Detecting Disease in Radiographs with Intuitive Confidence |
| title_fullStr | Detecting Disease in Radiographs with Intuitive Confidence |
| title_full_unstemmed | Detecting Disease in Radiographs with Intuitive Confidence |
| title_short | Detecting Disease in Radiographs with Intuitive Confidence |
| title_sort | detecting disease in radiographs with intuitive confidence |
| url | http://dx.doi.org/10.1155/2015/946793 |
| work_keys_str_mv | AT stefanjaeger detectingdiseaseinradiographswithintuitiveconfidence |