Public articles linked to the same research event.
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery This article reviews advances in applying artificial intelligence across the full chain of head and neck tumor care from screening and diagnosis to follow-up management, noting that endoscopic images, CT/MRI imaging, digital pathology, ultrasound, and multi-omics data are the main data modalities, that AI-assisted endoscopic interpretation and imaging analysis can improve lesion recognition accuracy, reduce operator dependence, and support non-invasive prediction of occult lymph node metastasis, while current evidence comes mostly from single-center retrospective studies and prospective evidence for treatment response prediction remains limited.
This article reviews advances in applying artificial intelligence across the full chain of head and neck tumor care from screening and diagnosis to follow-up management, noting that endoscopic images, CT/MRI imaging, digital pathology, ultrasound, and multi-omics data are the main data modalities, that AI-assisted endoscopic interpretation and imaging analysis can improve lesion recognition accuracy, reduce operator dependence, and support non-invasive prediction of occult lymph node metastasis, while current evidence comes mostly from single-center retrospective studies and prospective evidence for treatment response prediction remains limited.
This article reviews advances in applying artificial intelligence across the full chain of head and neck tumor care from screening and diagnosis to follow-up management, noting that endoscopic images, CT/MRI imaging, digital pathology, ultrasound, and multi-omics data are the main data modalities, that AI-assisted endoscopic interpretation and imaging analysis can improve lesion recognition accuracy, reduce operator dependence, and support non-invasive prediction of occult lymph node metastasis, while current evidence comes mostly from single-center retrospective studies and prospective evidence for treatment response prediction remains limited.
This article reviews advances in applying artificial intelligence across the full chain of head and neck tumor care from screening and diagnosis to follow-up management, noting that endoscopic images, CT/MRI imaging, digital pathology, ultrasound, and multi-omics data are the main data modalities, that AI-assisted endoscopic interpretation and imaging analysis can improve lesion recognition accuracy, reduce operator dependence, and support non-invasive prediction of occult lymph node metastasis, while current evidence comes mostly from single-center retrospective studies and prospective evidence for treatment response prediction remains limited.