Analysis of Deep Learning Techniques for Dental Informatics: A Systematic Literature Review.
Healthcare (Basel)
; 10(10)2022 Sep 28.
Article
in English
| MEDLINE | ID: covidwho-2110001
ABSTRACT
Within the ever-growing healthcare industry, dental informatics is a burgeoning field of study. One of the major obstacles to the health care system's transformation is obtaining knowledge and insightful data from complex, high-dimensional, and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, heterogeneous, poorly documented, and generally unstructured electronic health records, imaging, sensor data, and text. There were still certain restrictions even after many current techniques were used to extract more robust and useful elements from the data for analysis. New effective paradigms for building end-to-end learning models from complex data are provided by the most recent deep learning technology breakthroughs. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for dental informatics problems and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to some drawbacks and the need for better technique development and provide new perspectives about this exciting new development in the field.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Reviews
/
Systematic review/Meta Analysis
Language:
English
Year:
2022
Document Type:
Article
Affiliation country:
Healthcare10101892
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