Эпидемиология и факторы риска рака шейки матки

ФАКТОРЫ РИСКАШЕЙКИ МАТКИ НОВООБРАЗОВАНИ

Smart homes and their users:a systematic analysis and key challenges

Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home-functional, instrumental, socio-technical; (2) users and the use of the smart home-prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home-hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns-privacy and control-that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified

Diagnostic and prognostic value of noninvasive long-term video-electroencephalographic monitoring in epilepsy surgery: A systematic review and meta-analysis from the E-PILEPSY consortium

OBJECTIVE: The European Union–funded E‐PILEPSY network (now continuing within the European Reference Network for rare and complex epilepsies [EpiCARE]) aims to harmonize and optimize presurgical diagnostic procedures by creating and implementing evidence‐based guidelines across Europe. The present study evaluates the current evidence on the diagnostic accuracy of long‐term video‐electroencephalographic monitoring (LTM) in identifying the epileptogenic zone in epilepsy surgery candidates. METHODS: MEDLINE, Embase, CENTRAL, and ClinicalTrials.gov were searched for relevant articles. First, we used random‐effects meta‐analytical models to calculate pooled estimates of sensitivity and specificity with respect to postsurgical seizure freedom. In a second phase, we analyzed individual patient data in an exploratory fashion, assessing diagnostic accuracy within lesional and nonlesional temporal lobe epilepsy (TLE) and extratemporal lobe epilepsy (ETLE) patients. We also evaluated seizure freedom rate in the presence of “localizing” or “nonlocalizing” LTM within each group. The quality of evidence was assessed using the QUADAS‐2 tool and the GRADE approach. RESULTS: Ninety‐four studies were eligible. Forty‐four were included in sensitivity meta‐analysis and 34 in specificity meta‐analysis. Pooled sensitivity was 0.70 (95% confidence interval [CI] = 0.60‐0.80) and specificity was 0.40 (95% CI = 0.27‐0.54). Subgroup analysis was based on individual data of 534 patients (41% men). In lesional TLE patients, sensitivity was 0.85 (95% CI = 0.81‐0.89) and specificity was −0.19 (95% CI = 0.13‐0.28). In lesional ETLE patients, a sensitivity of 0.47 (95% CI = 0.36‐0.58) and specificity of 0.35 (95% CI = 0.21‐0.53) were observed. In lesional TLE, if LTM was localizing and concordant with resection site, the seizure freedom rate was 247 of 333 (74%), whereas in lesional ETLE it was 34 of 56 (61%). The quality of evidence was assigned as “very low.” SIGNIFICANCE: Long‐term video‐electroencephalographic monitoring is associated with moderate sensitivity and low specificity in identification of the epileptogenic zone. Sensitivity is remarkably higher in lesional TLE compared to lesional ETLE. Substantial heterogeneity across the studies indicates the need for improved design and quality of reporting

SeismoTracker: Upgrade any smart Wearable to enable a sensing of heart rate, respiration rate, and microvibrations

In this paper we present a method to enable any smart Wearable to sense vital data in resting states. These resting states (e.g. sleeping, sitting calmly, etc.) imply the presence of low-amplitude body-motions. Our approach relies on seismocardiography (SCG), which only requires a built-in accelerometer. Compared to commonly applied technologies, such as photoplethysmography (PPG), our approach is not only tracking heart rate (HR), but also respiration rate (RR), and microvibrations (MV) of the muscles, while being also computational inexpensive. In addition, we can calculate several other parameters, such as HR variability and RR variability. Our extracted vital parameters match with the vital data gathered from clinical state-of-the art technology. These data allow us to gain an impression on the user's activity, quality of sleep, arousal and stress level over the whole day, week, month, or year. Moreover, we can detect whether a device is actually worn or doffed, which is crucial when connecting such data with health services. We implemented our method on two current smartwatches: a Simvalley AW420 RX as well as on a LG G Watch R and recorded user data for several months. A web platform enables to keep track of one's data

Characterization of CMOS metal based dielectric loaded surface plasmon waveguides at telecom wavelengths

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