Comparative analysis of Ki-67 labeling index morphometry using deep learning, conventional image analysis, and manual counting.

The Ki-67 labeling index is essential for predicting the prognosis of breast cancer and for diagnosing neuroendocrine and gastrointestinal stromal tumors. However, current manual counting and digital image analysis (DIA)-based methods are limited in terms of accurate estimation. This study aimed to assess and compare the capabilities of different DIA systems for Ki-67 counting using the conventional manual counting method.

Factors associated with regular dental attendance by aged adults: A systematic review.

Objectives: To determine factors influencing regular dental attendance in aged adults 65 and over according to Andersen's Behavioural Model.

Background: Regular attendance for dental visits is vital to improve and maintain oral health, quality of life and general well-being. Aged adults 65 years and older experience barriers to regular dental attendance, which in turn leads to an increased risk for oral diseases.