Work

Artificial Intelligence–Assisted reflectance confocal microscopy for Real-Time intraoperative margin assessment in oral squamous cell carcinoma

Year: 2026

Type: article

Study design: Observational Study

Source: Oral Oncology

DOI: 10.1016/j.oraloncology.2026.107939

Authors: Farideh Hosseinzadeh, Daniella Zanoni, Paula Demétrio de Souza França, Cristina Valero, Gary Peterson, Marco Ardigo, Ronald Ghossein, Stephen W. Dusza, Nagavarakishore Pillarsetty, Kivanc Kose, Richard J. Wong, Ian Ganly, Milind Rajadhyaksha, Snehal G. Patel

Institutions: Memorial Sloan Kettering Cancer Center, Medical University of South Carolina, University of Wisconsin–Madison, Hospital de Sant Pau, IRCCS Humanitas Research Hospital

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Cancer Institute

Awards: Confocal video-mosaicking microscopy to guide surgery of superficially spreading skin cancers, Fiber bundle-based divided-pupil confocal endoscope, Reflectance confocal microscopy-optical coherence tomography (RCM-OCT) imaging of oral lesions: Toward an affordable device and approach for developing countries

OpenAlex ID: W7148596728

FWCI: 10.19

Cites: 12

Cited by: 3

Related to: 10