Age Assessment through Root Lengths of Mandibular Second and Third Permanent Molars Using Machine Learning and Artificial Neural Networks.

The present study explores the efficacy of Machine Learning and Artificial Neural Networks in age assessment using the root length of the second and third molar teeth. A dataset of 1000 panoramic radiographs with intact second and third molars ranging from 12 to 25 years was archived. The length of the mesial and distal roots was measured using ImageJ software. The dataset was classified in three ways based on the age distribution: 2-Class, 3-Class, and 5-Class. We used Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression models to train, test, and analyze the root length measurements. The mesial root of the third molar on the right side was a good predictor of age. The SVM showed the highest accuracy of 86.4% for 2-class, 66% for 3-class, and 42.8% for 5-Class. The RF showed the highest accuracy of 47.6% for 5-Class. Overall the present study demonstrated that the Deep Learning model (fully connected model) performed better than the Machine Learning models, and the mesial root length of the right third molar was a good predictor of age. Additionally, a combination of different root lengths could be informative while building a Machine Learning model.

Transforming healthcare through a digital revolution: A review of digital healthcare technologies and solutions.

The COVID-19 pandemic has put a strain on the entire global healthcare infrastructure. The pandemic has necessitated the re-invention, re-organization, and transformation of the healthcare system. The resurgence of new COVID-19 virus variants in several countries and the infection of a larger group of communities necessitate a rapid strategic shift. Governments, non-profit, and other healthcare organizations have all proposed various digital solutions. It's not clear whether these digital solutions are adaptable, functional, effective, or reliable. With the disease becoming more and more prevalent, many countries are looking for assistance and implementation of digital technologies to combat COVID-19. Digital health technologies for COVID-19 pandemic management, surveillance, contact tracing, diagnosis, treatment, and prevention will be discussed in this paper to ensure that healthcare is delivered effectively. Artificial Intelligence (AI), big data, telemedicine, robotic solutions, Internet of Things (IoT), digital platforms for communication (DC), computer vision, computer audition (CA), digital data management solutions (blockchain), digital imaging are premiering to assist healthcare workers (HCW's) with solutions that include case base surveillance, information dissemination, disinfection, and remote consultations, along with many other such interventions.