A simple AI-enabled method for quantifying bacterial adhesion on dental materials.

Ding, Hao; Yang, Yunzhen; Li, Xin; Cheung, Gary Shun-Pan; Matinlinna, Jukka Pekka; Burrow, Michael; Tsoi, James Kit-Hon

Ding, Hao; Yang, Yunzhen; Li, Xin; Cheung, Gary Shun-Pan; Matinlinna, Jukka Pekka; Burrow, Michael; Tsoi, James Kit-Hon.

Afiliación

Ding H; Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong Kong.
Yang Y; Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong Kong.
Li X; Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong Kong.
Cheung GS; Department of Stomatology Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen, China.
Matinlinna JP; Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong Kong.
Burrow M; Dental Materials Science, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong Kong.
Tsoi JK; Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong, Pokfulam, Hong Kong.

Biomater Investig Dent ; 9(1): 75-83, 2022.

Article en En | MEDLINE | ID: mdl-36081491

Palabras clave

Bacteria; PMMA; artificial intelligence; dental materials; zirconia

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Biomater Investig Dent Año: 2022 Tipo del documento: Article País de afiliación: Hong Kong

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google