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Lite image analysis module ‘A boon in the field of salivary diagnosis’
Author(s) -
Jayanta Saikia,
Dipshikha Das
Publication year - 2020
Publication title -
dental poster journal
Language(s) - English
Resource type - Journals
ISSN - 2278-7372
DOI - 10.15713/ins.dpj.063
Subject(s) - field (mathematics) , computer science , image (mathematics) , artificial intelligence , computer graphics (images) , computer vision , mathematics , pure mathematics
Commentary: Cancer, cardiovascular, metabolic, and neurological diseases disturb the bodily mechanism of an individual, causing a devastating impact on a global scale. Therefore, the diagnosis of such diseases at an early pace is important. An early diagnosis relies on both a thorough clinical evaluation and precise laboratory investigations. Most clinical samples are collected through invasive procedures. The past decade has seen a surge in the development of non-invasive salivary diagnostic1. In addition to local changes with the oral cavity, the salivary samples have also shown to exhibit alteration in response to several systemic diseases including cancer. They have also been used in forensics to screen for drugs2. Saliva acts as a mirror of an individual’s health3 containing various hormones, protein, enzymes that can eventually detect a disease. As mentioned earlier, compared to blood investigations, the medium of collection of saliva is simple, non-invasive, and largely reduces the risk of infection as the individual can collect the saliva without the need for a healthcare provider4,5. Within the past few decades, the field of salivary diagnostics has reached a stupendous peak. One such example is the Litebox Image Analysis Module (LIAMTM), a portable handheld device holds a promising potential for delivering immediate results from salivary samples collected in the field.

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