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The conception of measures to prevent illnesses acquired by patients when they are hospitalized, called Hospital Acquired Complications (HACs), are a challenge these days. Prevention can be achieved through the creation of standard policies and procedures to be followed by hospital agents, as well as by algorithmic analyzes of available hospitalization data, to anticipate cases of HACs. This work extends the preprocessing phase of an application of the machine-learning model for predicting the occurrence of HACs using temporal clinical data. The original work achieved good results in the analysis phase, but they argue that it would be necessary to increase the volume of data with which the results were made so that those results could be generalized. They used the MIMIC II database (Multiparameter Intelligent Monitoring in Intensive Care) and this work aims to convert the application developed to make use of the MIMIC III (Medical Information Mart for Intensive Care) database, which has a much larger data volume. However, this article focuses only on the preprocessing phase. The conversion was successful and the application now retrieves data from the MIMC III according to the needs of the prediction model. The next step of this work is to use the retrieved data and re-test the original model and verify the possibility of generalization of the results. [ABSTRACT FROM AUTHOR]

Medical Database include all the essential information to predict, diagnosis and make decision about treatment to any disease, but we cannot recognize the hidden knowledge with nude eyes. We need microscope to do its works, so we use data mining method clustering as microscope on medical database to extract hidden knowledge which will be helpful to medical domain. Applying Conceptual clustering is an important way of summarizing data. This paper focuses on HAC method of clustering to analyze food borne diseases & help medical domain to take decision on those disease. The goal is to find knowledge of disease causation, to prevent and control disease, and to help administrative guidance. [ABSTRACT FROM PUBLISHER]

In this paper, novel antenna design concepts and chip-package-board co-design methodology are shown to demonstrate MediaTek's R&D activities in microwave. Various antenna technologies of broadband, low HAC (hearing-aid compatibility), and higher efficiency are developed for better OTA (over-the-air) performance. A co-design methodology, which integrates the aggressor, victim, and coupling path model into a single platform, is also presented to deal with system level desensitization problems in system-on-chip (SoC) and system-in-package (SiP) designs. With these key design considerations and methodology, MediaTek provides a reliable platform with good wireless performance guaranteed, and keeps being the pioneer in the microwave research and industry. [ABSTRACT FROM PUBLISHER]