Niha Khan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Niha Khan has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Abdul Ahmed
Department of Prosthodontics, College of Dentistry King Khalid University, Abha, Saudi Arabia
1 shared publication - Afsheen Maqsood
Department of Oral Pathology, Bahria University Dental College, Karachi 75530, Pakistan
1 shared publication - Anand Marya
Department of Orthodontics, Faculty of Dentistry, University of Puthisastra, Phnom Penh, Cambodia
1 shared publication - Artak Heboyan
Department of Research Analytics Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University Chennai India
1 shared publication - Gotam Das
Department of Prosthodontics, College of Dentistry, King Khalid University, Abha, Saudi Arabia
1 shared publication - Maria Shakoor Abbasi
Prosthodontics Department, School of Dentistry Shaheed Zulfiqar Ali Bhutto Medical University Islamabad Pakistan
1 shared publication
Latest Publications
- Open Access
- 5 December 2022
- Published by MDPI AG in Healthcare
- Vol. 10 (12) , 2454
Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review
This study aimed to analyze the existing literature on how artificial intelligence is being used to support the identification of cephalometric landmarks. The systematic analysis of literature was carried out by performing an extensive search in PubMed/MEDLINE, Google Scholar, Cochrane, Scopus, and Science Direct databases. Articles published in the last ten years were selected after applying the inclusion and exclusion criteria. A total of 17 full-text articles were systematically appraised. The Cochrane Handbook for Systematic Reviews of Interventions (CHSRI) and Newcastle-Ottawa quality assessment scale (NOS) were adopted for quality analysis of the included studies. The artificial intelligence systems were mainly based on deep learning-based convolutional neural networks (CNNs) in the included studies. The majority of the studies proposed that AI-based automatic cephalometric analyses provide clinically acceptable diagnostic performance. They have worked remarkably well, with accuracy and precision similar to the trained orthodontist. Moreover, they can simplify cephalometric analysis and provide a quick outcome in practice. Therefore, they are of great benefit to orthodontists, as with these systems they can perform tasks more efficiently.
- 5 December 2022
- Published by MDPI AG in Healthcare
- Vol. 10 (12) , 2454
Open AccessDevelopment, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review
This study aimed to analyze the existing literature on how artificial intelligence is being used to support the identification of cephalometric landmarks. The systematic analysis of literature was carried out by performing an extensive search in PubMed/MEDLINE, Google Scholar, Cochrane, Scopus, and Science Direct databases. Articles published in the last ten years were selected after applying the inclusion and exclusion criteria. A total of 17 full-text articles were systematically appraised. The Cochrane Handbook for Systematic Reviews of Interventions (CHSRI) and Newcastle-Ottawa quality assessment scale (NOS) were adopted for quality analysis of the included studies. The artificial intelligence systems were mainly based on deep learning-based convolutional neural networks (CNNs) in the included studies. The majority of the studies proposed that AI-based automatic cephalometric analyses provide clinically acceptable diagnostic performance. They have worked remarkably well, with accuracy and precision similar to the trained orthodontist. Moreover, they can simplify cephalometric analysis and provide a quick outcome in practice. Therefore, they are of great benefit to orthodontists, as with these systems they can perform tasks more efficiently.