Diş Hekimliği Öğrencilerinin Yapay Zeka Hakkında Bilgi Düzeylerinin İncelenmesi

Objective: The present study was conducted to investigate the knowledge of dental students about artificial intelligence (AI) in healthcare.Methods: This study utilized a descriptive online survey, where respondents completed a Survey Monkey® questionnaire that evaluated their perceptions and opinions regarding the integration of AI in dentistry. The survey questionnaire included 20 questions designed to assess participants' demographic characteristics and their comprehension of AI.Results: The study involved a total of 226 student participants, with 31.4% (n:71) being first-year students, 15.5% (n:35) second-year, 23.5% (n:53) third-year, 11.1% (n:25) fourth-year, and 18.6% (n:42) fifth-year students. The average age of the participants was 20.86±3.40, and 66.4% were female. 97.3% of participants (n:220) had prior knowledge of AI, while just 68.1% (n:154) reported no concerns regarding AI. 58.4% (n:132) of students said they had no knowledge of AI applications in dentistry, while 92.5% (n:209) expressed a desire to use AI in their future practice. Less than half of the participants said they were informed about AI, while 90.7% thought it should be included in the curriculum. There was no statistically significant difference in understanding of the use of AI in dentistry between the fourth and fifth grades compared to the first grades.Conclusion: This study concluded that students' knowledge about AI was insufficient and revealed that upper-grade students had more knowledge about the areas of AI usage in dentistry compared to lower-grades.

Authors

Publication Details

Journal
DergiPark (Istanbul University)
Published
2024-08-04
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diş Hekimliği Öğrencilerinin Yapay Zeka Hakkında Bilgi Düzeylerinin İncelenmesi

Sanaz Sadry, Dilara Güngören Altundağ, Asel Üsdat Öztürk
DergiPark (Istanbul University)
Artificial Intelligence in Healthcare and Education
article

Diş Hekimliği Öğrencilerinin Yapay Zeka Hakkında Bilgi Düzeylerinin İncelenmesi

Sanaz Sadry, Dilara Güngören Altundağ, Asel Üsdat Öztürk
article en

Abstract

Objective: The present study was conducted to investigate the knowledge of dental students about artificial intelligence (AI) in healthcare.Methods: This study utilized a descriptive online survey, where respondents completed a Survey Monkey® questionnaire that evaluated their perceptions and opinions regarding the integration of AI in dentistry. The survey questionnaire included 20 questions designed to assess participants' demographic characteristics and their comprehension of AI.Results: The study involved a total of 226 student participants, with 31.4% (n:71) being first-year students, 15.5% (n:35) second-year, 23.5% (n:53) third-year, 11.1% (n:25) fourth-year, and 18.6% (n:42) fifth-year students. The average age of the participants was 20.86±3.40, and 66.4% were female. 97.3% of participants (n:220) had prior knowledge of AI, while just 68.1% (n:154) reported no concerns regarding AI. 58.4% (n:132) of students said they had no knowledge of AI applications in dentistry, while 92.5% (n:209) expressed a desire to use AI in their future practice. Less than half of the participants said they were informed about AI, while 90.7% thought it should be included in the curriculum. There was no statistically significant difference in understanding of the use of AI in dentistry between the fourth and fifth grades compared to the first grades.Conclusion: This study concluded that students' knowledge about AI was insufficient and revealed that upper-grade students had more knowledge about the areas of AI usage in dentistry compared to lower-grades.

DergiPark (Istanbul University)
Quality Education
Openalex Percentile: Top 55%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.