Artificial Intelligence for Early Detection and Diagnosis of Oral Cancer
This book analyzes using artificial intelligence (AI) for the purpose of oral cancer early detection. The book explores how advanced computer algorithms can analyze medical images, transcriptomic/epigenetic profiles, and relevant patient data to enhance early detection and accurate diagnosis of oral...
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| Autores principales: | , |
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| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Lenguaje: | inglés |
| Publicado: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edición: | 1st ed. 2025. |
| Colección: | Signals and Communication Technology,
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| Materias: | |
| Acceso en línea: | https://doi.org/10.1007/978-3-032-05056-4 |
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| 100 | 1 | |a Thanki, Rohit. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Artificial Intelligence for Early Detection and Diagnosis of Oral Cancer |h [electronic resource] / |c by Rohit Thanki, Sejal Shah. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
| 300 | |a 1 online resource (XV, 124 p. 43 illus.). |b 41 illus. in color. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 338 | |a online resource |b cr |2 rdacarrier | ||
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| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background color |2 onix | |
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| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
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| 490 | 1 | |a Signals and Communication Technology, |x 1860-4870 | |
| 505 | 0 | |a Introduction -- An Introduction to Oral Cancer -- Types, Diagnosis and Treatment of Oral Cancer -- Artificial Intelligence and Its Role in Early Detection of Oral Cancer -- Various Stages of Detection and Diagnosis of Oral Cancer using AI -- Current Research Treads for Early Screening of Oral Cancer using AI -- Conclusion. | |
| 520 | |a This book analyzes using artificial intelligence (AI) for the purpose of oral cancer early detection. The book explores how advanced computer algorithms can analyze medical images, transcriptomic/epigenetic profiles, and relevant patient data to enhance early detection and accurate diagnosis of oral cancer, to prevent death and disability, and improve quality of life. The book starts by providing a comprehensive overview of oral cancer, its risk factors, and the importance of early detection. It then delves into the fundamental concepts of AI and its application in healthcare. Readers will gain a deeper understanding of how AI algorithms can “see” patterns in oral cells and tissue, enabling the detection of abnormal cells and precancerous transcriptomic or epigenetic changes that may indicate the presence of oral cancer. This book intended for professionals, researchers, policymakers, and anyone interested in the intersection of AI and healthcare. Analyzes using artificial intelligence (AI) for the purpose of oral cancer early detection; Explores how algorithms can analyze data and images to enhance early detection and accurate diagnosis of oral cancer; Highlights AI in risk assessment, personalized screening strategies, and decision support for healthcare professionals. | ||
| 532 | 8 | |a Accessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Telecommunication. | |
| 650 | 0 | |a Biomedical engineering. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Medical informatics. | |
| 650 | 1 | 4 | |a Communications Engineering, Networks. |
| 650 | 2 | 4 | |a Biomedical Engineering and Bioengineering. |
| 650 | 2 | 4 | |a Machine Learning. |
| 650 | 2 | 4 | |a Health Informatics. |
| 700 | 1 | |a Shah, Sejal. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 830 | 0 | |a Signals and Communication Technology, |x 1860-4870 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-032-05056-4 |
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| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||
| 950 | |a Focus Bundle Electrical and Electronic Engineering (SpringerNature-85403) | ||