No abstract

No abstract

BACKGROUND: Intravascular ultrasound (IVUS) is an invasive imaging modality that provides high resolution crosssectional images permitting detailed evaluation of the lumen, outer vessel wall and plaque morphology and evaluation of its composition. Over the last years several methodologies have been proposed which allow automated processing of the IVUS data and reliable segmentation of the regions of interest or characterization of the type of the plaque. OBJECTIVE: In this paper we present a novel methodology for the automated identification of different plaque components in grayscale IVUS images. METHODS: The proposed method is based on a hybrid approach that incorporates both image processing techniques and classification algorithms and allows classification of the plaque into three different categories: Hard Calcified, Hard-Non Calcified and Soft plaque. Annotations by two experts on 8 IVUS examinations were used to train and test our method. RESULTS: The combination of an automatic thresholding technique and active contours coupled with a Random Forest classifier provided reliable results with an overall classification accuracy of 86.14%. CONCLUSIONS: The proposed method can accurately detect the plaque using grayscale IVUS images and can be used to assess plaque composition for both clinical and research purposes.

Over the last 30 years, diabetes mellitus has changed from being seen as a relatively mild ailment associated with aging and the elderly ("just a touch of sugar") to one of the major contemporary causes of premature mortality and morbidity in most countries. In virtually every developed society, diabetes is ranked among the leading causes of blindness, renal failure, and lower limb amputation. Through its effects on cardiovascular disease (70%-80% of people with diabetes die of cardiovascular disease), it is also now one of the leading causes of death. Even diabetes mellitus seems to be dealt with due to innovative information and communication technologies, along with new forms of service delivery organization such as home care and remote monitoring. This paper provides a review of the innovative concept of using mobile phones for diabetes monitoring starting with a brief introduction, continuing with an analysis of health and lifestyle related data that record the patient-health-professional's interaction and decision making, and concluding with a general discussion section followed by an extended bibliography.

In this paper, we describe the serious games, integrated into PROPHETIC which is an innovating personal healthcare service for a holistic remote management of Parkinson’s disease (PD) patients. The main objective of the three developed serious games is to allow health professionals to remotely monitor and appraise the overall physical status of their patients. The significant benefits for the patients, making use of this platform, is the improvement of their engagement, empowerment and, consequently, the provision of education about their condition and its management. The design of the serious games was based on the clinical needs derived from the literature and their primary target is to assess and record specific physical capabilities of the patient. All the games scores and the recorded parameters are gathered and also presented to the clinicians, offering them a precise overview of the patient’s motor status and the possibility to modify the therapeutic plan, if required.

No abstract

Pediatric Central Nervous System (CNS) neoplasms are the second most prevalent tumors of childhood. Further on, prognosis of this type of neoplasms still remain poor and the comprehension of the etiology and pathogenesis of the disease still remains scarce. Several reports have identified microRNAs as significant molecules in the development of central nervous system tumors and propose that they might compose key molecules underlying oncogenesis. In a previous study we have identified several miRNAs, common to different subtypes of pediatric embryonal CNS malignancies as well as, we have identified miRNAs that manifest significant dynamics with respect to their expression and the neoplasmatic subtype. Overall, 19 tumor cases from children diagnosed with embryonal brain tumors were investigated. As controls, children who suffered a sudden death underwent autopsy and were not present with any brain malignancy were used (13 samples of varying localization). Our experimental approach included microarrays covering 1211 miRNAs, which appeared to manifest tumor-specific dynamics. In conclusion, it appeared that certain miRNAs are neoplasm specific and in particular, their expression manifests linear dynamics. Thus, the investigation of miRNA expression in pediatric embryonal brain tumors might contribute towards the discovery of tumor-specific miRNA signatures, which could potentially afford the identification of gene-specific biomarkers related to diagnosis, prognosis and patient targeted therapy, as well as help us understand oncogenetic dynamics.

This paper presents the architecture and implementation of an automatic medication dispenser (iMedPlus) specifically for users who take medications without close professional supervision. By relieving the users from the error-prone tasks of interpreting medication directions and administrating medications accordingly, the device can improve rigor in compliance and prevent serious medication errors. By taking advantage of scheduling flexibility provided by medication directions, the device makes the user’s medication schedule easy to adhere and tolerant to tardiness whenever possible. This work is done collaboratively by the medication scheduler and dispenser controller in an action-oriented manner. An advantage of the action-oriented interface between the components is extensibility, as new functions can be added and existing ones removed with little or no need to modify the dispenser control structure. The paper first describes the action-oriented design, major components, and hardware structures of the smart device. It then provides an overview of the heuristic algorithms used by the medication scheduler and their relative merits. The different available user options are presented depicting the user-specific operating modes of the device/service. The scope of this paper is to describe the development of a smart electronic drug dispenser unit for the pharmaceutical adherence of patients.