A comprehensive operating room information system using the Kinect sensors and RFID.

Occasionally, surgeons do need various types of information to be available rapidly, efficiently and safely during surgical procedures. Meanwhile, they need to free up hands throughout the surgery to necessarily access the mouse to control any application in the sterility mode. In addition, they are required to record audio as well as video files, and enter and save some data. This is an attempt to develop a comprehensive operating room information system called "Medinav" to tackle all mentioned issues. An integrated and comprehensive operating room information system is introduced to be compatible with Health Level 7 (HL7) and digital imaging and communications in medicine (DICOM). DICOM is a standard for handling, storing, printing, and transmitting information in medical imaging. Besides, a natural user interface (NUI) is designed specifically for operating rooms where touch-less interactions with finger and hand tracking are in use. Further, the system could both record procedural data automatically, and view acquired information from multiple perspectives graphically. A prototype system is tested in a live operating room environment at an Iranian teaching hospital. There are also contextual interviews and usability satisfaction questionnaires conducted with the "MediNav" system to investigate how useful the proposed system could be. The results reveal that integration of these systems into a complete solution is the key to not only stream up data and workflow but maximize surgical team usefulness as well. It is now possible to comprehensively collect and visualize medical information, and access a management tool with a touch-less NUI in a rather quick, practical, and harmless manner.

Developing a genetic fuzzy system for risk assessment of mortality after cardiac surgery.

Cardiac events could be taken into account as the leading causes of death throughout the globe. Such events also trigger an undesirable increase in what treatment procedures cost. Despite the giant leaps in technological development in heart surgery, coronary surgery still carries the high risk of the mortality. Besides, there is still a long way ahead to accurately predict and assess the mortality risk. This study is an attempt to develop an expert system for the risk assessment of mortality following the cardiac surgery. The developed system involves three main steps. In the first step, a filtering feature selection method is applied to select the best features. In the second step, an ad hoc data-driven method is utilized to generate the preliminary fuzzy inference system. Finally, a hybrid optimization method is presented to select the optimum subset of the rules. The study relies on 1,811 samples to evaluate the diagnosis performance of the proposed system. The obtained classification accuracy is very promising with regard to other benchmark classification methods including binary logistic regression (LR) and multilayer perceptron neural network (MLP) with the same attributes. The developed system leads to 100% sensitivity and 84.7% specificity, while LR and MLP methods statistically come up with lower figures (65, 78.6 and 65%, 75.8%), respectively. Now, a fuzzy supportive tool can be potentially taken as an alternative for the current mortality risk assessment system that are applied in coronary surgeries, and are chiefly based on crisp database.

Mathematical modeling of transmission dynamics and optimal control of vaccination and treatment for hepatitis B virus.

Hepatitis B virus (HBV) infection is a worldwide public health problem. In this paper, we study the dynamics of hepatitis B virus (HBV) infection which can be controlled by vaccination as well as treatment. Initially we consider constant controls for both vaccination and treatment. In the constant controls case, by determining the basic reproduction number, we study the existence and stability of the disease-free and endemic steady-state solutions of the model. Next, we take the controls as time and formulate the appropriate optimal control problem and obtain the optimal control strategy to minimize both the number of infectious humans and the associated costs. Finally at the end numerical simulation results show that optimal combination of vaccination and treatment is the most effective way to control hepatitis B virus infection.

Fuzzy modeling and control of HIV infection.

The present study proposes a fuzzy mathematical model of HIV infection consisting of a linear fuzzy differential equations (FDEs) system describing the ambiguous immune cells level and the viral load which are due to the intrinsic fuzziness of the immune system's strength in HIV-infected patients. The immune cells in question are considered CD4+ T-cells and cytotoxic T-lymphocytes (CTLs). The dynamic behavior of the immune cells level and the viral load within the three groups of patients with weak, moderate, and strong immune systems are analyzed and compared. Moreover, the approximate explicit solutions of the proposed model are derived using a fitting-based method. In particular, a fuzzy control function indicating the drug dosage is incorporated into the proposed model and a fuzzy optimal control problem (FOCP) minimizing both the viral load and the drug costs is constructed. An optimality condition is achieved as a fuzzy boundary value problem (FBVP). In addition, the optimal fuzzy control function is completely characterized and a numerical solution for the optimality system is computed.