Artificial Tuberculosis

Diagnosis of Pulmonary Tuberculosis Using Artificial Intelligence (Naive Bayes Algorithm)

Background and Aim: Despite the implementation of effective preventive and therapeutic programs, no significant success has been achieved in the reduction of tuberculosis. One of the reasons is the delay in diagnosis. Therefore, the creation of a diagnostic aid system can help to diagnose early Tuberculosis. The purpose of this research was to evaluate the role of the Naive Bayes algorithm as a...

Artificial Pneumothorax in Pulmonary Tuberculosis

The Artificial Pneumothorax Treatment of Pulmonary Tuberculosis

realised in India. It is disappointing to note, however, that its importance is being underrated by a certain section of the medical profession who probably do so not from any personal experience of it, but rather from a lack of knowledge of its technique and mode of action. It appears that with them the treatment of phthisis begins and ends with fresh air and good food. They forget that fresh ...

Tuberculosis control, and the where and why of artificial intelligence

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a s...

Predicting active pulmonary tuberculosis using an artificial neural network.

BACKGROUND Nosocomial outbreaks of tuberculosis (TB) have been attributed to unrecognized pulmonary TB. Accurate assessment in identifying index cases of active TB is essential in preventing transmission of the disease. OBJECTIVES To develop an artificial neural network using clinical and radiographic information to predict active pulmonary TB at the time of presentation at a health-care faci...