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Artificial intelligence for image recognition in diagnosing oral and oropharyngeal cancer and leukoplakia.
Sci Rep
January 2025
Department of Otolaryngology Head and Neck Surgery, Technical University Munich, Munich, Germany.
Visual diagnosis is one of the key features of squamous cell carcinoma of the oral cavity (OSCC) and oropharynx (OPSCC), both subsets of head and neck squamous cell carcinoma (HNSCC) with a heterogeneous clinical appearance. Advancements in artificial intelligence led to Image recognition being introduced recently into large language models (LLMs) such as ChatGPT 4.0.
View Article and Find Full Text PDFIs postoperative adjuvant therapy necessary for pT3N0 oral cavity squamous cell carcinoma?
Oral Oncol
January 2025
Department of Otorhinolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital and Chang Gung University Taoyuan Taiwan Republic of China. Electronic address:
Background: The current NCCN guidelines advocate for the use of adjuvant radiotherapy (RT) or chemoradiotherapy (CRT) in pT3N0 oral cavity squamous cell carcinoma (OCSCC). Here, we sought to evaluate whether postoperative RT/CRT may confer a survival advantage in pT3N0 patients who lack adverse pathological features.
Methods: A dataset of 852 pT3N0 OCSCC patients treated between 2018 and 2021 was analyzed.
A multi-scale information fusion medical image segmentation network based on convolutional kernel coupled updata mechanism.
Comput Biol Med
January 2025
State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China. Electronic address:
Medical image segmentation is pivotal in disease diagnosis and treatment. This paper presents a novel network architecture for medical image segmentation, termed TransDLNet, which is engineered to enhance the efficiency of multi-scale information utilization. TransDLNet integrates convolutional neural networks and Transformers, facilitating cross-level multi-scale information fusion for complex medical images.
View Article and Find Full Text PDFOptimizing dental implant identification using deep learning leveraging artificial data.
Sci Rep
January 2025
Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Kagawa University, 1750-1, Ikenobe, Miki-cho, Kita-gun, Takamatsu, 761-0793, Kagawa, Japan.
This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using panoramic X-ray images. To supplement an existing dataset of 7,946 in vivo dental implant images, a three-dimensional scanner was employed to create implant surface models. Subsequently, implant surface models were used to generate two-dimensional X-ray images, which were compiled along with original images to create a comprehensive dataset.
View Article and Find Full Text PDFEnhancing immunotherapy efficacy in oral cancer through AKB-9778-mediated vascular normalization.
Int Immunopharmacol
January 2025
State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China; Department of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Wuhan University, Wuhan 430079, China. Electronic address:
Tumor vasculature exhibit numerous abnormal features distinct from those of healthy vessels, potentially advancing tumor development by establishing an aberrant microenvironment. Therefore, vascular normalization has proven to be an effective tactic for substantially enhancing treatment efficacy across multiple tumors. However, the methods to attain vascular normalization may vary among tumor types.
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