objectives in order to increase the classification accuracy of airs, this study introduces a new hybrid system that incorporates a support vector machine into airs for diagnosing tuberculosis. background tuberculosis (tb) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. diagnosis based on cultured specimens is the...

Pathology is the gold standard for clinical diagnosis and an important bridge between work basic disciplines. Therefore, training qualified pathologists very work. It challenging to diagnose lymphohematopoietic diseases in practice since they made up a large percentage of resident doctors’ standardized there are numerous knowledge nodes associated with them. this base adopts “case-introduction”...

Smart grid has been introduced to address power distribution system challenges. In conventional power distribution systems, when a power outage happens, the maintenance team tries to find the outage cause and mitigate it. After this, some information is documented in a dataset called the outage dataset. If the team can estimate the outage cause before searching for it, the restoration time will...

In artificial intelligence, deep learning (DL) is a process that replicates the working mechanism of human brain in data processing, and it also creates patterns for decision making. Deep or neural networks have been deployed several fields, such as computer vision, natural language speech recognition. It has used many healthcare applications diagnosis treatment chronic diseases. These algorith...

The diagnosis of lung diseases is a complicated and time-consuming task for radiologists. Often radiologists struggle with accurately diagnosing diseases, They use Commonly CT imaging signs (CISs) which common appear in nodules the diseases. Computer-aided systems (CAD) can automatically diagnose detect these by analyzing scans, will reduce workload. recognition efficiency accuracy be improved ...