Falk Schwendicke1, Tarry Singh2, Jae-Hong Lee3, Robert Gaudin4, Akhilanand Chaurasia5, Thomas Wiegand6, Sergio Uribe7, Joachim Krois8. 1. Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Berlin, Germany; ITU/WHO Focus Group AI on Health, Topic Group Dentistry, Switzerland. Electronic address: falk.schwendicke@charite.de. 2. ITU/WHO Focus Group AI on Health, Topic Group Dentistry, Switzerland; Visiting Faculty AI, University of Dallas, Texas, United States. 3. ITU/WHO Focus Group AI on Health, Topic Group Dentistry, Switzerland; Department of Periodontology, Daejeon Dental Hospital, Institute of Wonkwang Dental Research, Wonkwang University College of Dentistry, Daejeon, Republic of Korea. 4. Department of Maxillofacial Surgery, Charité - Universitätsmedizin Berlin, Berlin, Germany. 5. Department of Oral Medicine and Radiology, King George's Medical University., Lucknow, India. 6. Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Berlin, Germany; ITU/WHO Focus Group AI on Health, Topic Group Dentistry, Switzerland; Visiting Faculty AI, University of Dallas, Texas, United States; Department of Periodontology, Daejeon Dental Hospital, Institute of Wonkwang Dental Research, Wonkwang University College of Dentistry, Daejeon, Republic of Korea; Department of Maxillofacial Surgery, Charité - Universitätsmedizin Berlin, Berlin, Germany; Department of Oral Medicine and Radiology, King George's Medical University., Lucknow, India. 7. ITU/WHO Focus Group AI on Health, Topic Group Dentistry, Switzerland; Conservative Dentistry and Oral Health Dept and Bioinformatics Research Unit, Riga Stradins University, Riga, Latvia; School of Dentistry, Universidad Austral de Chile, Valdivia, Chile. 8. Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Berlin, Germany; ITU/WHO Focus Group AI on Health, Topic Group Dentistry, Switzerland.
Abstract
OBJECTIVES: The number of studies employing artificial intelligence (AI), specifically machine and deep learning, is growing fast. The majority of studies suffer from limitations in planning, conduct and reporting, resulting in low robustness, reproducibility and applicability. We here present a consented checklist on planning, conducting and reporting of AI studies for authors, reviewers and readers in dental research. METHODS: Lending from existing reviews, standards and other guidance documents, an initial draft of the checklist and an explanatory document were derived and discussed among the members of IADR's e-oral network and the ITU/WHO focus group "Artificial Intelligence for Health (AI4H)". The checklist was consented by 27 group members via an e-Delphi process. RESULTS: Thirty-one items on planning, conducting and reporting of AI studies were agreed on. These involve items on the studies' wider goal, focus, design and specific aims, data sampling and reporting, sample estimation, reference test construction, model parameters, training and evaluation, uncertainty and explainability, performance metrics and data partitions. CONCLUSION: Authors, reviewers and readers should consider this checklist when planning, conducting, reporting and evaluating studies on AI in dentistry. CLINICAL SIGNIFICANCE: Current studies on AI in dentistry show considerable weaknesses, hampering their replication and application. This checklist may help to overcome this issue and advance AI research as well as facilitate a debate on standards in this fields.
OBJECTIVES: The number of studies employing artificial intelligence (AI), specifically machine and deep learning, is growing fast. The majority of studies suffer from limitations in planning, conduct and reporting, resulting in low robustness, reproducibility and applicability. We here present a consented checklist on planning, conducting and reporting of AI studies for authors, reviewers and readers in dental research. METHODS: Lending from existing reviews, standards and other guidance documents, an initial draft of the checklist and an explanatory document were derived and discussed among the members of IADR's e-oral network and the ITU/WHO focus group "Artificial Intelligence for Health (AI4H)". The checklist was consented by 27 group members via an e-Delphi process. RESULTS: Thirty-one items on planning, conducting and reporting of AI studies were agreed on. These involve items on the studies' wider goal, focus, design and specific aims, data sampling and reporting, sample estimation, reference test construction, model parameters, training and evaluation, uncertainty and explainability, performance metrics and data partitions. CONCLUSION: Authors, reviewers and readers should consider this checklist when planning, conducting, reporting and evaluating studies on AI in dentistry. CLINICAL SIGNIFICANCE: Current studies on AI in dentistry show considerable weaknesses, hampering their replication and application. This checklist may help to overcome this issue and advance AI research as well as facilitate a debate on standards in this fields.
Authors: Reinhard Chun Wang Chau; Ming Chong; Khaing Myat Thu; Nate Sing Po Chu; Mohamad Koohi-Moghadam; Richard Tai-Chiu Hsung; Colman McGrath; Walter Yu Hang Lam Journal: PLoS One Date: 2022-06-02 Impact factor: 3.752
Authors: Naseer Ahmed; Maria Shakoor Abbasi; Filza Zuberi; Warisha Qamar; Mohamad Syahrizal Bin Halim; Afsheen Maqsood; Mohammad Khursheed Alam Journal: Biomed Res Int Date: 2021-06-22 Impact factor: 3.411
Authors: Luis Oala; Andrew G Murchison; Pradeep Balachandran; Shruti Choudhary; Jana Fehr; Alixandro Werneck Leite; Peter G Goldschmidt; Christian Johner; Elora D M Schörverth; Rose Nakasi; Martin Meyer; Federico Cabitza; Pat Baird; Carolin Prabhu; Eva Weicken; Xiaoxuan Liu; Markus Wenzel; Steffen Vogler; Darlington Akogo; Shada Alsalamah; Emre Kazim; Adriano Koshiyama; Sven Piechottka; Sheena Macpherson; Ian Shadforth; Regina Geierhofer; Christian Matek; Joachim Krois; Bruno Sanguinetti; Matthew Arentz; Pavol Bielik; Saul Calderon-Ramirez; Auss Abbood; Nicolas Langer; Stefan Haufe; Ferath Kherif; Sameer Pujari; Wojciech Samek; Thomas Wiegand Journal: J Med Syst Date: 2021-11-02 Impact factor: 4.920