AI Medical Compendium Topic

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Mouth Neoplasms

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Deep multiple instance learning versus conventional deep single instance learning for interpretable oral cancer detection.

PloS one
The current medical standard for setting an oral cancer (OC) diagnosis is histological examination of a tissue sample taken from the oral cavity. This process is time-consuming and more invasive than an alternative approach of acquiring a brush sampl...

Length of Stay Prediction Models for Oral Cancer Surgery: Machine Learning, Statistical and ACS-NSQIP.

The Laryngoscope
OBJECTIVE: Accurate prediction of hospital length of stay (LOS) following surgical management of oral cavity cancer (OCC) may be associated with improved patient counseling, hospital resource utilization and cost. The objective of this study was to c...

Deep neural network uncertainty estimation for early oral cancer diagnosis.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
BACKGROUND: Early diagnosis in oral cancer is essential to reduce both morbidity and mortality. This study explores the use of uncertainty estimation in deep learning for early oral cancer diagnosis.

Applying Machine Learning for Enhanced MicroRNA Analysis: A Companion Risk Tool for Oral Squamous Cell Carcinoma in Standard Care Incisional Biopsy.

Biomolecules
Machine learning analyses within the realm of oral cancer outcomes are relatively underexplored compared to other cancer types. This study aimed to assess the performance of machine learning algorithms in identifying oral cancer patients, utilizing m...

Application of deep learning radiomics in oral squamous cell carcinoma-Extracting more information from medical images using advanced feature analysis.

Journal of stomatology, oral and maxillofacial surgery
OBJECTIVE: To conduct a systematic review with meta-analyses to assess the recent scientific literature addressing the application of deep learning radiomics in oral squamous cell carcinoma (OSCC).

Machine learning methods in predicting the risk of malignant transformation of oral potentially malignant disorders: A systematic review.

International journal of medical informatics
BACKGROUND: Oral Potentially Malignant Disorders (OPMDs) refer to a heterogenous group of clinical presentations with heightened rate of malignant transformation. Identification of risk levels in OPMDs is crucial to determine the need for active inte...

A deep learning method for multi-task intelligent detection of oral cancer based on optical fiber Raman spectroscopy.

Analytical methods : advancing methods and applications
In the fight against oral cancer, innovative methods like Raman spectroscopy and deep learning have become powerful tools, particularly in integral tasks encompassing tumor staging, lymph node staging, and histological grading. These aspects are esse...