Automated Analysis of Nuclear Parameters in Oral Exfoliative Cytology Using Machine Learning.

Background: As oral cancer remains a major worldwide health concern, sophisticated diagnostic tools are needed to aid in early diagnosis. Non-invasive methods like exfoliative cytology, albeit with the help of artificial intelligence (AI), have drawn additional interest.

Aim: The study aimed to harness the power of machine learning algorithms for the automated analysis of nuclear parameters in oral exfoliative cytology.

Post Surgical Non-tuberculous Mycobacterium: A Case Series.

Background There has been an increase in non-tuberculous mycobacteria (NTM) infection reports in humans. Surgeons are concerned about the link between them and surgical site infections. As a result, it has been challenging to determine just how common this illness is.