Classification of coronary artery disease severity based on SPECT MPI polarmap images and deep learning: A study on multi-vessel disease prediction.

Background: Coronary artery disease (CAD) is a global health concern. Conventional single photon emission computed tomography myocardial perfusion imaging (SPECT MPI) is a noninvasive method for assessing the severity of CAD. However, it relies on manual classification by clinicians, which can lead to visual fatigue and potential errors.

Deep learning for myocardial ischemia auxiliary diagnosis using CZT SPECT myocardial perfusion imaging.

Background: The World Health Organization reported that cardiovascular disease is the most common cause of death worldwide. On average, one person dies of heart disease every 26 min worldwide. Deep learning approaches are characterized by the appropriate combination of abnormal features based on numerous annotated images.

A CMMI-based approach for medical software project life cycle study.

In terms of medical techniques, Taiwan has gained international recognition in recent years. However, the medical information system industry in Taiwan is still at a developing stage compared with the software industries in other nations. In addition, systematic development processes are indispensable elements of software development.

Applying ontology techniques to develop a medication history search and alert system in department of nuclear medicine.

Nowadays, patients usually take more than three drugs for diseases such as hypertension, diabetes, and dyslipidemia. Hence, nuclear medicine physicians should be very careful about the medication history of each patient and ensure that their medication will not cause false positive or false negative imaging results, because either condition will interfere with adequate treatment of the patient and result in a wrong diagnosis. The aim of the present paper is to develop an ontology-based medication search and alert system for scintiphotography of Chang Gung Memorial hospital at Kaohsiung.