Skin cancer classification based on an optimized convolutional neural network and multicriteria decision-making.

Skin cancer is a type of cancer disease in which abnormal alterations in skin characteristics can be detected. It can be treated if it is detected early. Many artificial intelligence-based models have been developed for skin cancer detection and classification.

A hybrid model for the detection of retinal disorders using artificial intelligence techniques.

The prevalence of vision impairment is increasing at an alarming rate. The goal of the study was to create an automated method that uses optical coherence tomography (OCT) to classify retinal disorders into four categories: choroidal neovascularization, diabetic macular edema, drusen, and normal cases. This study proposed a new framework that combines machine learning and deep learning-based techniques.

An integrative approach to medical laboratory equipment risk management.

Medical Laboratory Equipment (MLE) is one of the most influential means for diagnosing a patient in healthcare facilities. The accuracy and dependability of clinical laboratory testing is essential for making disease diagnosis. A risk-reduction plan for managing MLE is presented in the study.

Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach.

The purchase of medical equipment is a critical issue that should be planned properly. The selection of the most appropriate vendor impacts time, effort, and expenses. Therefore, the challenge is to strike a balance between the available budget and the required equipment.

Computer-aided diagnosis system for retinal disorder classification using optical coherence tomography images.

The incidence of vision impairment is rapidly increasing. Diagnosis and classifying retinal abnormalities in ophthalmological applications is a significant challenge. Using Optical Coherence Tomography (OCT), the study aims to develop a computer aided diagnosis system for detecting and classifying retinal disorders.

An integrated assessment system for the accreditation of medical laboratories.

Medical laboratory accreditation becomes a trend to be trustable for diagnosis of diseases. It is always performed at regular intervals to assure competence of quality management systems (QMS) based on pre-defined standards. However, few attempts were carried out to assess the quality level of medical laboratory services.

Automated Risk Control in Medical Imaging Equipment Management Using Cloud Application.

Medical imaging equipment (MIE) is the baseline of providing patient diagnosis in healthcare facilities. However, that type of equipment poses high risk for patients, operators, and environment in terms of technology and application. Considering risk management in MIE management is rarely covered in literature.

Comprehensive framework for preventive maintenance priority of medical equipment.

Throughout the medical equipment life cycle, preventive maintenance is considered one of the most important stages that should be managed properly. However, the need for better management and control by giving a reasonable prioritization for preventive maintenance becomes essential. The purpose of this study is to develop a comprehensive framework for preventive maintenance priority of medical equipment using Quality Function Deployment (QFD) and Fuzzy Logic (FL).

Preventive maintenance prioritization index of medical equipment using quality function deployment.

Preventive maintenance is a core function of clinical engineering, and it is essential to guarantee the correct functioning of the equipment. The management and control of maintenance activities are equally important to perform maintenance. As the variety of medical equipment increases, accordingly the size of maintenance activities increases, the need for better management and control become essential.