Artificial Intelligence in Dentistry
| dc.contributor.author | Cagiltay, Nergiz Ercil | |
| dc.contributor.author | Kılıçarslan, Mehmet Ali | |
| dc.contributor.author | Basmaci, Fulya | |
| dc.date.accessioned | 2025-09-05T15:56:50Z | |
| dc.date.available | 2025-09-05T15:56:50Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Today, with advanced technologies, collecting detailed and big data from the environment and analyzing it using intelligent techniques has become possible, providing important insights into phenomena as well as future predictions. Big data is characterized by its high volume, velocity, and variety. Here, the volume is the amount and size of the data, which is measured in terabytes, petabytes, exabytes, or zettabytes. Velocity is the offered form of big data, which can be batch, near-real-time, real-time, or streaming. Finally, variety is the structure of the big data, which can be structured, such as in relational or dimensional models, as in warehouses, or unstructured, which is stored without any organization. It can also be in semi-structured form, where the data is unstructured but there is some meta-data or some tags for describing the data. Today, these forms of data are being collected for different dental purposes in several formats, such as images, raw data, or coordinates. © 2025 Elsevier B.V., All rights reserved. | en_US |
| dc.identifier.doi | 10.1201/9781003531449-10 | |
| dc.identifier.isbn | 9781032830513 | |
| dc.identifier.isbn | 9781040439401 | |
| dc.identifier.scopus | 2-s2.0-105013372915 | |
| dc.identifier.uri | https://doi.org/10.1201/9781003531449-10 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12416/10345 | |
| dc.language.iso | en | en_US |
| dc.publisher | CRC Press | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Artificial Intelligence | en_US |
| dc.subject | Big Data | en_US |
| dc.subject | Advanced Technology | en_US |
| dc.subject | Dimensional Model | en_US |
| dc.subject | Future Predictions | en_US |
| dc.subject | High Volumes | en_US |
| dc.subject | Intelligent Techniques | en_US |
| dc.subject | Near-Real Time | en_US |
| dc.subject | Petabytes | en_US |
| dc.subject | Real- Time | en_US |
| dc.subject | Relational Modeling | en_US |
| dc.subject | Volume Velocities | en_US |
| dc.subject | Dentistry | en_US |
| dc.title | Artificial Intelligence in Dentistry | en_US |
| dc.type | Book Part | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Çağıltay, Nergiz | |
| gdc.author.scopusid | 16237826800 | |
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| gdc.description.department | Çankaya University | en_US |
| gdc.description.departmenttemp | [Cagiltay] Nergiz Ercil, Çankaya Üniversitesi, Ankara, Turkey; [Kılıçarslan] Mehmet Ali, Ankara Üniversitesi, Ankara, Turkey; [Basmaci] Fulya, Ankara Yildirim Beyazit University, Ankara, Turkey | en_US |
| gdc.description.endpage | 211 | en_US |
| gdc.description.publicationcategory | Kitap Bölümü - Uluslararası | en_US |
| gdc.description.scopusquality | N/A | |
| gdc.description.startpage | 193 | en_US |
| gdc.description.wosquality | N/A | |
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