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With the rapid growth of data sources, Big data security in Cloud is a big challenge. Different issues have ascended in the area of Big data security such as infrastructure security, data privacy, data management and data integrity. Currently, Big data processing, analytics and storage is secured using cryptography algorithms, which are not appropriate for Big data protection over Cloud. In this paper, we present a solution for addressing the main issues in Big data security over Cloud. We propose a novel system architecture called the Secure Authentication and Data Sharing in Cloud (SADS-Cloud). There are three processes involved in this paper including (i). Big Data Outsourcing, (ii). Big Data Sharing and (iii). Big Data Management. In Big data outsourcing, the data owners are registered to a Trust Center using SHA-3 hashing algorithm. The MapReduce model is used to split the input file into fixed-size of blocks of data and SALSA20 encryption algorithm is applied over each block. In Big data sharing, data users participate in a secure file retrieval. For this purpose, user's credentials (ID, password, secure ID, and current timestamp, email id) are hashed and compared with that stored in a database. In Big data management, there are three important processes implemented to organize data. They are as follows: Compression using Lemperl Ziv Markow Algorithm (LZMA), Clustering using Density-based Clustering of Applications with Noise (DBSCAN), and Indexing using Fractal Index Tree. The proposed scheme for these processes are implemented using Java Programming and performance tested for the following metrics: Information Loss, Compression Ratio, Throughput, Encryption Time and Decryption Time.

Aim: The aim of the study was to establish the feasibility of delivering a structured post‐diagnosis information and support program to dyads (persons living with dementia or mild cognitive impairment and family carers) in two primary care settings. Design: A two‐phase explanatory mixed‐method approach guided by the Bowen Feasibility Framework focused on acceptability, implementation, adaptation, integration and efficacy of a five‐part programme. In phase 1, the quantitative impact of the programme on the dyadic programme recipients' self‐efficacy, quality of life, dyadic relationship and volume of care was measured. In phase 2, inductive content analysis focused on nurse and dyad participant experiences of the programme. Quantitative and qualitative data were reviewed to conclude each element of feasibility. Methods: Four registered nurses working within the participating sites were recruited, trained as programme facilitators and supported to deliver the programme. Eligible dyads attending the respective primary health clinics were invited to participate in the programme and complete surveys at three time points: recruitment, post‐programme and 3‐month follow‐up. Post‐programme semi‐structured interviews were conducted with dyads and programme facilitators. Results: Twenty‐nine dyads completed the program; the majority were spousal dyads. The programme proved acceptable to the dyads with high retention and completion rates. Implementation and integration of the programme into usual practice were attributed to the motivation and capacity of the nurses as programme facilitators. Regarding programme efficacy, most dyads reported they were better prepared for the future and shared the plans they developed during the programme with family members. Conclusion: Implementing a structured information and support programme is feasible, but sustainability requires further adaptation or increased staff resources to maintain programme fidelity. Future research should consider selecting efficacy measures sensitive to the unique needs of people living with dementia and increasing follow‐up time to 6 months. Impact: This study established the feasibility of registered nurses delivering a post‐diagnosis information and support programme for people living with early‐stage dementia or mild cognitive impairment and their informal carers in primary care settings.The motivation and capacity of nurses working as programme facilitators ensured the integration of the programme into usual work, but this was not considered sustainable over time.Family carer dyads reported tangible outcomes and gained confidence in sharing their diagnosis with family and friends and asking for assistance.Findings from this study can be used to provide direction for a clinical trial investigating the effectiveness of the structured information and support programme in the primary care setting. Reporting Method: The authors have adhered to the EQUATOR STROBE Statement. Patient or Public Contribution: A public hospital memory clinic and general medical practice participated in project design, study protocol development and supported implementation. [ABSTRACT FROM AUTHOR]

Background: A range of strategies are available that can improve the outcomes of older persons particularly in relation to basic activities of daily living during and after an acute care (AC) episode. This paper outlines the original development of outcome-oriented quality indicators (QIs) in relation to common geriatric syndromes and function for the care of the frail aged hospitalized in acute general medical wards. Methods: Design QIs were developed using evidence from literature, expert opinion, field study data and a formal voting process. A systematic literature review of literature identified existing QIs (there were no outcome QIs) and evidence of interventions that improve older persons' outcomes in AC. Preliminary indicators were developed by two expert panels following consideration of the evidence. After analysis of the data from field testing (indicator prevalence, variability across sites), panel meetings refined the QIs prior to a formal voting process. Setting: Data was collected in nine Australian general medical wards. Participants: Patients aged 70 years and over, consented within 24 h of admission to the AC ward. Measurements: The interRAI Acute Care – Comprehensive Geriatric Assessment (interRAI AC-CGA) was administered at admission and discharge; a daily risk assessment in hospital; 28-day phone follow-up and chart audit. Results: Ten outcome QIs were established which focused on common geriatric syndromes and function for the care of the frail aged hospitalized in acute general medical wards. Conclusion: Ten outcome QIs were developed. These QIs can be used to identify areas where specific action will lead to improvements in the quality of care delivered to older persons in hospital. [ABSTRACT FROM AUTHOR]

The paper proposes a novel scheme for color image watermarking. Spatial domain techniques are used here for embedding the watermark information to generate high quality watermarked image. Spatial domain methods are popular with fragile watermarking techniques that mostly use two or three least significant image bits for storing the recovery information. Here spatial domain methods are further explored to develop a robust mechanism for copyright protection. The method presented gradually spreads the watermark information over a region of pixels as implemented by the transform domain techniques. Thus the method is designed to deliver the two essential features required of watermarking systems namely, high image quality and high robustness to attacks. Also after watermark embedding it is ensured that the alterations in one color component are well compensated and no color difference or variations is visually evident. For watermark embedding and color compensation two masks are proposed. The algorithm is experimentally analyzed using various quality metrics and watermark removal attacks. The results prove the model support imperceptible watermarking and high resilience to attacks. Keywords: Color image watermarking, Spatial domain, Watermark, Embedding, Extraction, Attacks

Human disease identification from the scanned body parts helps medical practitioners make the right decision in lesser time. Image segmentation plays a vital role in automated diagnosis for the delineation of anatomical organs and anomalies. There are many variants of segmentation algorithms used by current researchers, whereas there is no universal algorithm for all medical images. This paper classifies some of the widely used medical image segmentation algorithms based on their evolution, and the features of each generation are also discussed. The comparative analysis of segmentation algorithms is done based on characteristics like spatial consideration, region continuity, computation complexity, selection of parameters, noise immunity, accuracy, and computation time. Finally, in this work, some of the typical segmentation algorithms are implemented on real-time datasets using Matlab 2010 software, and the outcome of this work will be an aid for the researchers in medical image processing.

Objective High-throughput phenotyping will accelerate the use of electronic health records (EHRs) for translational research. A critical roadblock is the extensive medical supervision required for phenotyping algorithm (PA) estimation and evaluation. To address this challenge, numerous weakly-supervised learning methods have been proposed. However, there is a paucity of methods for reliably evaluating the predictive performance of PAs when a very small proportion of the data is labeled. To fill this gap, we introduce a semi-supervised approach (ssROC) for estimation of the receiver operating characteristic (ROC) parameters of PAs (eg, sensitivity, specificity). Materials and Methods ssROC uses a small labeled dataset to nonparametrically impute missing labels. The imputations are then used for ROC parameter estimation to yield more precise estimates of PA performance relative to classical supervised ROC analysis (supROC) using only labeled data. We evaluated ssROC with synthetic, semi-synthetic, and EHR data from Mass General Brigham (MGB). Results ssROC produced ROC parameter estimates with minimal bias and significantly lower variance than supROC in the simulated and semi-synthetic data. For the 5 PAs from MGB, the estimates from ssROC are 30% to 60% less variable than supROC on average. Discussion ssROC enables precise evaluation of PA performance without demanding large volumes of labeled data. ssROC is also easily implementable in open-source R software. Conclusion When used in conjunction with weakly-supervised PAs, ssROC facilitates the reliable and streamlined phenotyping necessary for EHR-based research. [ABSTRACT FROM AUTHOR]

The detection of uterine abnormalities in the early stage is challenging and it aims to play a vital role in automated screening systems. The algorithm proposed herein works in the following way: initially a PDE (Partial Differential Equation approach) based speckle reduction is carried out in a preprocessing stage, and the region of interest is separated from the female pelvic ultrasound images. Then the texture and shape features are extracted from the segmented ROI component. The results of shape similarity indices between manual and automated segmentations are also illustrated. The simulation result analysis of this algorithm was implemented in MATLAB R2016a. In this paper, an automatic segmentation scheme is proposed which will aid the radiologists for better outputs in very limited time making the proposed solution very effective and productive. Keywords: Speckle, Segmentation, Tumor, Feature extraction and ultrasound imaging