AIMC Topic: Saliva
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Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time.
The Analyst
Nov 4, 2024
With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first ...
Salivary detection of Chikungunya virus infection using a portable and sustainable biophotonic platform coupled with artificial intelligence algorithms.
Scientific reports
Sep 16, 2024
The current detection method for Chikungunya Virus (CHIKV) involves an invasive and costly molecular biology procedure as the gold standard diagnostic method. Consequently, the search for a non-invasive, more cost-effective, reagent-free, and sustain...
Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta.
International journal of molecular sciences
Aug 30, 2024
Amelogenesis imperfecta (AI) is a genetic disease characterized by poor formation of tooth enamel. AI occurs due to mutations, especially in AMEL, ENAM, KLK4, MMP20, and FAM83H, associated with changes in matrix proteins, matrix proteases, cell-matri...
A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence.
Nature communications
Jun 15, 2024
Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires complex processing steps and human annotation. Here we developed an artificial intelligence (AI)-powered automated framework for ready detection of vir...
Raman hyperspectroscopy of saliva and machine learning for Sjögren's disease diagnostics.
Scientific reports
May 15, 2024
Sjögren's disease is an autoimmune disorder affecting exocrine glands, causing dry eyes and mouth and other morbidities. Polypharmacy or a history of radiation to the head and neck can also lead to dry mouth. Sjogren's disease is often underdiagnosed...
The potential value of oral microbial signatures for prediction of oral squamous cell carcinoma based on machine learning algorithms.
Head & neck
May 2, 2024
OBJECTIVE: This study aimed to explore the potential predictive value of oral microbial signatures for oral squamous cell carcinoma (OSCC) risk based on machine learning algorithms.
Can oral microbiome predict low birth weight infant delivery?
Journal of dentistry
Apr 27, 2024
OBJECTIVES: This study aimed to identify the oral microbiota factors contributing to low birth weight (LBW) in Chinese pregnant women and develop a prediction model using machine learning.
Developing an interpretation model for body fluid identification.
Forensic science international
Apr 22, 2024
Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to provide context. In most cases this can be achieved by conventional methods, however, in certain scenar...
Prediction of xerostomia in elderly based on clinical characteristics and salivary flow rate with machine learning.
Scientific reports
Feb 10, 2024
Xerostomia may be accompanied by changes in salivary flow rate and the incidence increases in elderly. We aimed to use machine learning algorithms, to identify significant predictors for the presence of xerostomia. This study is the first to predict ...
Psychological Alterations in Youths with Type I Diabetes: Associations with Salivary Cortisol Concentration.
Medicina (Kaunas, Lithuania)
Dec 21, 2023
Type 1 diabetes mellitus (T1DM) is one of the most common chronic diseases in children and adolescents, and is associated with stress and other psychological alterations. This study aims to assess psychological and sleep disorders and health-related...
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