Artificial intelligence in use of ZrO2 material in biomedical science
The rapidly growing discipline of artificial intelligence (AI) seeks to develop software and computers that can do tasks that have historically required the intelligence of people. Machine learning (ML) is a subfield of AI that makes use of algorithms to "learn" from data's innate st...
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| Format: | Article |
| Language: | English |
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International Association of Physical Chemists (IAPC)
2022-10-01
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| Series: | Journal of Electrochemical Science and Engineering |
| Subjects: | |
| Online Access: | https://pub.iapchem.org/ojs/index.php/JESE/article/view/1498 |
| _version_ | 1828318820154998784 |
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| author | Jashanpreet Singh Simranjit Singh Amit Verma |
| author_facet | Jashanpreet Singh Simranjit Singh Amit Verma |
| author_sort | Jashanpreet Singh |
| collection | DOAJ |
| description |
The rapidly growing discipline of artificial intelligence (AI) seeks to develop software and computers that can do tasks that have historically required the intelligence of people. Machine learning (ML) is a subfield of AI that makes use of algorithms to "learn" from data's innate statistical patterns and structures to extrapolate information that is otherwise hidden. A growing emphasis on cosmetic dentistry has coincided with ZrO2‘s rise to prominence as a result of its improved biocompatibility, visually pleasant look, strong oxidation resistance, better mechanical properties, and lack of documented allergic responses. Advances in the field of AI and ML have led to novel applications of ZrO2 in dental devices for biological objectives. Artificial intelligence (AI) technologies have attracted a lot of attention in ZrO2-related research and therapeutic applications due to their ability to analyze data and discover connections between seemingly unrelated events. Specifically, their incorporation into zirconia is largely responsible for this. Zirconia's versatility in the scientific community means that how AI is used in the area varies with the specific directions in which zirconia is utilized. Therefore, this article primarily focuses on the use of AI in the biomedical use of ZrO2 in dentistry.
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| first_indexed | 2024-04-13T17:47:46Z |
| format | Article |
| id | doaj.art-6a11986c53704623bae5d378f465b164 |
| institution | Directory Open Access Journal |
| issn | 1847-9286 |
| language | English |
| last_indexed | 2024-04-13T17:47:46Z |
| publishDate | 2022-10-01 |
| publisher | International Association of Physical Chemists (IAPC) |
| record_format | Article |
| series | Journal of Electrochemical Science and Engineering |
| spelling | doaj.art-6a11986c53704623bae5d378f465b1642022-12-22T02:36:50ZengInternational Association of Physical Chemists (IAPC)Journal of Electrochemical Science and Engineering1847-92862022-10-0110.5599/jese.1498Artificial intelligence in use of ZrO2 material in biomedical scienceJashanpreet Singh0Simranjit Singh1Amit Verma2Mechanical Engineering Department, Thapar University Patiala, 147004, IndiaDepartment of Computer Science and Engineering, Bennett University, Greater Noida 201310, IndiaDepartment of Computer Science, Chandigarh University, Mohali 140413, India The rapidly growing discipline of artificial intelligence (AI) seeks to develop software and computers that can do tasks that have historically required the intelligence of people. Machine learning (ML) is a subfield of AI that makes use of algorithms to "learn" from data's innate statistical patterns and structures to extrapolate information that is otherwise hidden. A growing emphasis on cosmetic dentistry has coincided with ZrO2‘s rise to prominence as a result of its improved biocompatibility, visually pleasant look, strong oxidation resistance, better mechanical properties, and lack of documented allergic responses. Advances in the field of AI and ML have led to novel applications of ZrO2 in dental devices for biological objectives. Artificial intelligence (AI) technologies have attracted a lot of attention in ZrO2-related research and therapeutic applications due to their ability to analyze data and discover connections between seemingly unrelated events. Specifically, their incorporation into zirconia is largely responsible for this. Zirconia's versatility in the scientific community means that how AI is used in the area varies with the specific directions in which zirconia is utilized. Therefore, this article primarily focuses on the use of AI in the biomedical use of ZrO2 in dentistry. https://pub.iapchem.org/ojs/index.php/JESE/article/view/1498Biomedical engineeringartificial intelligencemachine learningzirconia |
| spellingShingle | Jashanpreet Singh Simranjit Singh Amit Verma Artificial intelligence in use of ZrO2 material in biomedical science Journal of Electrochemical Science and Engineering Biomedical engineering artificial intelligence machine learning zirconia |
| title | Artificial intelligence in use of ZrO2 material in biomedical science |
| title_full | Artificial intelligence in use of ZrO2 material in biomedical science |
| title_fullStr | Artificial intelligence in use of ZrO2 material in biomedical science |
| title_full_unstemmed | Artificial intelligence in use of ZrO2 material in biomedical science |
| title_short | Artificial intelligence in use of ZrO2 material in biomedical science |
| title_sort | artificial intelligence in use of zro2 material in biomedical science |
| topic | Biomedical engineering artificial intelligence machine learning zirconia |
| url | https://pub.iapchem.org/ojs/index.php/JESE/article/view/1498 |
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