AIMC Topic: Mouth Neoplasms
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ChatGPT and oral cancer: a study on informational reliability.
BMC oral health
Jan 17, 2025
BACKGROUND: Artificial intelligence (AI) and large language models (LLMs) like ChatGPT have transformed information retrieval, including in healthcare. ChatGPT, trained on diverse datasets, can provide medical advice but faces ethical and accuracy co...
Advanced deep learning algorithms in oral cancer detection: Techniques and applications.
Journal of environmental science and health. Part C, Toxicology and carcinogenesis
Jan 17, 2025
As the 16 most common cancer globally, oral cancer yearly accounts for some 355,000 new cases. This study underlines that an early diagnosis can improve the prognosis and cut down on mortality. It discloses a multifaceted approach to the detection of...
Efficacy and empathy of AI chatbots in answering frequently asked questions on oral oncology.
Oral surgery, oral medicine, oral pathology and oral radiology
Jan 11, 2025
OBJECTIVES: Artificial intelligence chatbots have demonstrated feasibility and efficacy in improving health outcomes. In this study, responses from 5 different publicly available AI chatbots-Bing, GPT-3.5, GPT-4, Google Bard, and Claude-to frequently...
Diagnosis of lymph node metastasis in oral squamous cell carcinoma by an MRI-based deep learning model.
Oral oncology
Jan 2, 2025
BACKGROUND: Cervical lymph node metastasis (LNM) is a well-established poor prognosticator of oral squamous cell carcinoma (OSCC), in which occult metastasis is a subtype that makes prediction challenging. Here, we developed and validated a deep lear...
Attention-guided convolutional network for bias-mitigated and interpretable oral lesion classification.
Scientific reports
Dec 30, 2024
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for class...
Mucoepidermoid carcinoma: Enhancing diagnostic accuracy and treatment strategy through machine learning models and web-based prognostic tool.
Journal of stomatology, oral and maxillofacial surgery
Dec 25, 2024
BACKGROUND: Oral cancer, particularly mucoepidermoid carcinoma (MEC), presents diagnostic challenges due to its histological diversity and rarity. This study aimed to develop machine learning (ML) models to predict survival outcomes for MEC patients ...
Identifying threshold of CT-defined muscle loss after radiotherapy for survival in oral cavity cancer using machine learning.
European radiology
Dec 20, 2024
OBJECTIVES: Muscle loss after radiotherapy is associated with poorer survival in patients with oral cavity squamous cell carcinoma (OCSCC). However, the threshold of muscle loss remains unclear. This study aimed to utilize explainable artificial inte...
Performance of image processing analysis and a deep convolutional neural network for the classification of oral cancer in fluorescence visualization.
International journal of oral and maxillofacial surgery
Dec 12, 2024
The aim of this prospective study was to determine the effectiveness of screening using image processing analysis and a deep convolutional neural network (DCNN) to classify oral cancers using non-invasive fluorescence visualization. The study include...
Let it shine: Autofluorescence of Papanicolaou-stain improves AI-based cytological oral cancer detection.
Computers in biology and medicine
Dec 10, 2024
BACKGROUND AND OBJECTIVES: Oral cancer is a global health challenge. The disease can be successfully treated if detected early, but the survival rate drops significantly for late stage cases. There is a growing interest in a shift from the current st...
Development of an oral cancer detection system through deep learning.
BMC oral health
Dec 4, 2024
OBJECTIVE: We aimed to develop an AI-based model that uses a portable electronic oral endoscope to capture intraoral images of patients for the detection of oral cancer.
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