A simulation approach for scheduling patients in the department of radiation oncology.

Physical therapy, hemodialysis and radiation oncology departments in which patients go through lengthy and periodic treatments need to utilize their limited and expensive equipment and human resources efficiently. In such departments, it is an important task to continue to treat current patients without any interruption along with incoming patients. In this study, a patient scheduling approach for a university radiation oncology department is introduced to minimize delays in treatments due to potential prolongations in treatments of current patients and to maintain efficient use of the daily treatment capacity.

Neural network-based computer-aided diagnosis in classification of primary generalized epilepsy by EEG signals.

Epilepsy is a disorder of cortical excitability and still an important medical problem. The correct diagnosis of a patient's epilepsy syndrome clarifies the choice of drug treatment and also allows an accurate assessment of prognosis in many cases. The aim of this study is to classify subgroups of primary generalized epilepsy by using Multilayer Perceptron Neural Networks (MLPNNs).

A radial basis function neural network model for classification of epilepsy using EEG signals.

Epilepsy is a disorder of cortical excitability and still an important medical problem. The correct diagnosis of a patient's epilepsy syndrome clarifies the choice of drug treatment and also allows an accurate assessment of prognosis in many cases. The aim of this study is to evaluate epileptic patients and classify epilepsy groups such as partial and primary generalized epilepsy by using Radial Basis Function Neural Network (RBFNN) and Multilayer Perceptron Neural Network (MLPNNs).

Personnel and patient scheduling in the high demanded hospital services: a case study in the physiotherapy service.

High demand but limited staffs within some services of a hospital require a proper scheduling of staff and patients. In this study, a hierarchical mathematical model is proposed to generate weekly staff scheduling. Due to computational difficulty of this scheduling problem, the entire model is broken down into manageable three hierarchical stages: (1) selection of patients, (2) assignment of patients to the staff, (3) scheduling of patients throughout a day.

A radial basis function neural network (RBFNN) approach for structural classification of thyroid diseases.

The thyroid is a gland that controls key functions of body. Diseases of the thyroid gland can adversely affect nearly every organ in human body. The correct diagnosis of a patient's thyroid disease clarifies the choice of drug treatment and also allows an accurate assessment of prognosis in many cases.