Early Predicting Tribocorrosion Rate of Dental Implant Titanium Materials Using Random Forest Machine Learning Models.

Early detection and prediction of bio-tribocorrosion can avert unexpected damage that may lead to secondary revision surgery and associated risks of implantable devices. Therefore, this study sought to develop a state-of-the-art prediction technique leveraging machine learning(ML) models to classify and predict the possibility of mechanical degradation in dental implant materials. Key features considered in the study involving pure titanium and titanium-zirconium (zirconium = 5, 10, and 15 in wt%) alloys include corrosion potential, acoustic emission(AE) absolute energy, hardness, and weight-loss estimates.

Successful Management of an Occupational High-Voltage Electric Injury Associated With High-Risk Factors and a Clinically Significant Arrhythmia.

Electric injuries are uncommon but can lead to numerous long-term complications as well as death. Occupational exposure is the most common cause of injury among the affected population. Both low-voltage and high-voltage electrocution are associated with significant morbidity and mortality.

Assessment of the Financial Capacity in Elderly: Approach and Challenges in Indian Scenario.

The elderly population, with those individuals above the age of 60 years, is increasing exponentially, attributable to higher life expectancy as a result of improved health care, socioeconomic level, and quality of life. As they grow older (>80 years), it becomes difficult to manage their basic needs and daily living. A report on Decade of Healthy Ageing estimates that 14% of people aged 60 years and above cannot meet their basic daily needs which include the ability to manage finances.