Automated Diabetic Retinopathy Detection Using Horizontal and Vertical Patch Division-Based Pre-Trained DenseNET with Digital Fundus Images.

Diabetic retinopathy (DR) is a common complication of diabetes that can lead to progressive vision loss. Regular surveillance with fundal photography, early diagnosis, and prompt intervention are paramount to reducing the incidence of DR-induced vision loss. However, manual interpretation of fundal photographs is subject to human error.

Exemplar Darknet19 feature generation technique for automated kidney stone detection with coronal CT images.

Kidney stone is a commonly seen ailment and is usually detected by urologists using computed tomography (CT) images. It is difficult and time-consuming to detect small stones in CT images. Hence, an automated system can help clinicians to detect kidney stones accurately.

Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images.

COVID-19 and pneumonia detection using medical images is a topic of immense interest in medical and healthcare research. Various advanced medical imaging and machine learning techniques have been presented to detect these respiratory disorders accurately. In this work, we have proposed a novel COVID-19 detection system using an exemplar and hybrid fused deep feature generator with X-ray images.

Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and hinders people's vital activities. The majority of Parkinson's patients lose their ability to speak, write and balance.

Evaluation of prehospital emergency care in the field and during the ambulance drive to the hospital.

This study was conducted to evaluate the appropriateness of ambulance procedures and interventions in the management of patients dispatched to 2 emergency departments (EDs) of urban hospitals in Izmir. Use of trauma boards and cervical collars, airway patency, breathing, and circulation problems were recorded in both EDs. Eighty-one patients with a mean age of 47.