Presentation Date
January 9 & 10, 2023
Presenters
Morenike Ukpong
Maha El Tantawi
Nicolas Giraudeau
Ahmed Mahrous
Mona Ghoneim
Rania El Backly
Karim Fawzy
Moustafa Aboshelib
Hala Ali Maher
Moataz Khamis
Rania Afifi
Ahmed Mobarak
Ahmed Holeil
Hossam Mohamed
Marwan Ali
Sponsor Groups
e-Oral Health Network
CE Credits
3 CE Hours
Conflict of Interest Disclosure
None
January 9 & 10, 2023
Presenters
Morenike Ukpong
Maha El Tantawi
Nicolas Giraudeau
Ahmed Mahrous
Mona Ghoneim
Rania El Backly
Karim Fawzy
Moustafa Aboshelib
Hala Ali Maher
Moataz Khamis
Rania Afifi
Ahmed Mobarak
Ahmed Holeil
Hossam Mohamed
Marwan Ali
Sponsor Groups
e-Oral Health Network
CE Credits
3 CE Hours
Conflict of Interest Disclosure
None
Course Description:
Obtaining, organizing, and sorting primitive data related to patients and students’ records is a daily process in dental schools. Whether handwritten or digitally inserted, this data contains valuable information that when properly processed, could reveal lots of information and clues in relation to oral health of the patients and performance of dental students. In the last decade, data mining became an attractive science based on core principles that allows the process of finding anomalies, patterns and correlations within large data sets to predict outcomes of interest. Unstructured data alone makes up 90% of the digital universe, but more information does not necessarily mean more knowledge. Data mining allows us to shift through all the chaotic and repetitive noise in our data, understand what is relevant and assess likely outcomes, and accelerate the pace of making informed decisions.
Learning Objectives
Obtaining, organizing, and sorting primitive data related to patients and students’ records is a daily process in dental schools. Whether handwritten or digitally inserted, this data contains valuable information that when properly processed, could reveal lots of information and clues in relation to oral health of the patients and performance of dental students. In the last decade, data mining became an attractive science based on core principles that allows the process of finding anomalies, patterns and correlations within large data sets to predict outcomes of interest. Unstructured data alone makes up 90% of the digital universe, but more information does not necessarily mean more knowledge. Data mining allows us to shift through all the chaotic and repetitive noise in our data, understand what is relevant and assess likely outcomes, and accelerate the pace of making informed decisions.
Learning Objectives
- Concepts related to statistics and data analysis.
- Principles of descriptive, predictive, and prescriptive data modeling.
The International Association for Dental Research is an ADA CERP Recognized Provider. ADA CERP is a service of the American Dental Association to assist dental professionals in identifying quality providers of continuing dental education. ADA CERP does not approve or endorse individual courses or instructors, nor does it imply acceptance of credit hours by boards of dentistry. Concerns or complaints about a CE provider may be directed to the provider or to the Commission for Continuing Education Provider Recognition at ADA.org/CERP.
Complimentary Member Registration:
The Robotics & Artificial Intelligence: Targeting Oral Health Care in Africa in the Digital Age is open to all IADR members. Current IADR members can claim their complimentary registration today in the IADR Webinar & CE On Demand Library. Non-Members can join IADR to attend this virtual webinar.
