AIMC Topic: Mucositis

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Prediction of treatment outcome in burning mouth syndrome patients using machine learning based on clinical data.

Scientific reports Jul 28, 2021
The purpose of this study is to apply a machine learning approach to predict whether patients with burning mouth syndrome (BMS) respond to the initial approach and clonazepam therapy based on clinical data. Among the patients with the primary type of...
Humans Machine Learning Prognosis Female Male Middle Aged Treatment Outcome Burning Mouth Syndrome Lubricants Mucositis Clonazepam
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Microbiome Preprocessing Machine Learning Pipeline.

Frontiers in immunology Jun 18, 2021
BACKGROUND: 16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ...
Humans Neural Networks, Computer Machine Learning Pregnancy Female Adult Animals Phylogeny Mice Bacteria Progesterone Gastrointestinal Microbiome RNA, Ribosomal, 16S Hematopoietic Stem Cell Transplantation Interleukin-1alpha Colitis Mucositis
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Shotgun Metagenomics Identifies in a Cross-Sectional Setting Improved Plaque Microbiome Biomarkers for Peri-Implant Diseases.

Journal of clinical periodontology Jul 1, 2025
AIM: This observational study aimed to verify and improve the predictive value of plaque microbiome of patients with dental implant for peri-implant diseases.
Humans Machine Learning Biomarkers Female Aged Adult Cross-Sectional Studies Male Middle Aged Microbiota Dental Plaque Dental Implants Metagenomics Stomatitis Mucositis Peri-Implantitis
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