Sentiment analysis of health care tweets: review of the methods used.

BACKGROUND: Twitter is a microblogging service where users can send and read short 140-character messages called "tweets." There are several unstructured, free-text tweets relating to health care being shared on Twitter, which is becoming a popular area for health care research. Sentiment is a metric commonly used to investigate the positive or negative opinion within these messages. Exploring the methods used for sentiment analysis in Twitter health care research may allow us to better understand the options available for future research in this growing field. OBJECTIVE: The first objective of this study was to understand which tools would be available for sentiment analysis of Twitter health care research, by reviewing existing studies in this area and the methods they used. The second objective was to determine which method would work best in the health care settings, by analyzing how the methods were used to answer specific health care questions, their production, and how their accuracy was analyzed. METHODS: A review of the literature was conducted pertaining to Twitter and health care research, which used a quantitative method of sentiment analysis for the free-text messages (tweets). The study compared the types of tools used in each case and examined methods for tool production, tool training, and analysis of accuracy. RESULTS: A total of 12 papers studying the quantitative measurement of sentiment in the health care setting were found. More than half of these studies produced tools specifically for their research, 4 used open source tools available freely, and 2 used commercially available software. Moreover, 4 out of the 12 tools were trained using a smaller sample of the study's final data. The sentiment method was trained against, on an average, 0.45% (2816/627,024) of the total sample data. One of the 12 papers commented on the analysis of accuracy of the tool used. CONCLUSIONS: Multiple methods are used for sentiment analysis of tweets in the health care setting. These range from self-produced basic categorizations to more complex and expensive commercial software. The open source and commercial methods are developed on product reviews and generic social media messages. None of these methods have been extensively tested against a corpus of health care messages to check their accuracy. This study suggests that there is a need for an accurate and tested tool for sentiment analysis of tweets trained using a health care setting-specific corpus of manually annotated tweets first

Future broadband access network challenges

Copyright @ 2010 IEEEThe optical and wireless communication systems convergence will activate the potential capacity of photonic technology for providing the expected growth in interactive video, voice communication and data traffic services that are cost effective and a green communication service. The last decade growth of the broadband internet projects the number of active users will grow to over 2 billion globally by the end of 2014. Enabling the abandoned capacity of photonic signal processing is the promising solution for seamless transportation of the future consumer traffic demand. In this paper, the future traffic growth of the internet, wireless worldwide subscribers, and the end-users during the last and next decades is investigated. The challenges of the traditional access networks and Radio over Fiber solution are presented

The Preservation of Cued Recall in the Acute Mentally Fatigued State: A Randomised Crossover Study.

The objective of this study is to investigate the impact of acute mental fatigue on the recall of clinical information in the non-sleep-deprived state. Acute mental fatigue in the non-sleep-deprived subject is rarely studied in the medical workforce. Patient handover has been highlighted as an area of high risk especially in fatigued subjects. This study evaluates the deterioration in recall of clinical information over 2 h with cognitively demanding work in non-sleep-deprived subjects.A randomised crossover study involving twenty medical students assessed free (presentation) and cued (MCQ) recall of clinical case histories at 0 and 2 h under low and high cognitive load using the N-Back task. Acute mental fatigue was assessed through the Visual Analogue Scale, Stanford Scale and NASA-TLX Mental Workload Rating Scale.Free recall is significantly impaired by increased cognitive load (p < 0.05) with subjects demonstrating perceived mental fatigue during the high cognitive load assessment. There was no significant difference in the amount of information retrieved by cued recall under high and low cognitive load conditions (p = 1).This study demonstrates the loss of clinical information over a short time period involving a mentally fatiguing, high cognitive load task. Free recall for the handover of clinical information is unreliable. Memory cues maintain recall of clinical information. This study provides evidence towards the requirement for standardisation of a structured patient handover. The use of memory cues (involving recognition memory and cued recall methodology) would be beneficial in a handover checklist to aid recall of clinical information and supports evidence for their adoption into clinical practice

Free-View, 3D Gaze-Guided, Assistive Robotic System for Activities of Daily Living

Patients suffering from quadriplegia have limited body motion which prevents them from performing daily activities. We have developed an assistive robotic system with an intuitive free-view gaze interface. The user's point of regard is estimated in 3D space while allowing free head movement and is combined with object recognition and trajectory planning. This framework allows the user to interact with objects using fixations. Two operational modes have been implemented to cater for different eventualities. The automatic mode performs a pre-defined task associated with a gaze-selected object, while the manual mode allows gaze control of the robot's end-effector position on the user's frame of reference. User studies reported effortless operation in automatic mode. A manual pick and place task achieved a success rate of 100% on the users' first attempt.Comment: 7 Pages, 9 Figures, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018), Madrid, Spai

Fifty Years of Innovation in Plastic Surgery

© 2016 The Korean Society of Plastic and Reconstructive Surgeons.Background Innovation has molded the current landscape of plastic surgery. However, documentation of this process only exists scattered throughout the literature as individual articles. The few attempts made to profile innovation in plastic surgery have been narrative, and therefore qualitative and inherently biased. Through the implementation of a novel innovation metric, this work aims to identify and characterise the most prevalent innovations in plastic surgery over the last 50 years. Methods Patents and publications related to plastic surgery (1960 to 2010) were retrieved from patent and MEDLINE databases, respectively. The most active patent codes were identified and grouped into technology areas, which were subsequently plotted graphically against publication data. Expert-derived technologies outside of the top performing patents areas were additionally explored. Results Between 1960 and 2010, 4,651 patents and 43,118 publications related to plastic surgery were identified. The most active patent codes were grouped under reconstructive prostheses, implants, instruments, non-invasive techniques, and tissue engineering. Of these areas and other expert-derived technologies, those currently undergoing growth include surgical instruments, implants, non-invasive practices, transplantation and breast surgery. Innovations related to microvascular surgery, liposuction, tissue engineering, lasers and prostheses have all plateaued. Conclusions The application of a novel metric for evaluating innovation quantitatively outlines the natural history of technologies fundamental to the evolution of plastic surgery. Analysis of current innovation trends provides some insight into which technology domains are the most active

Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate

With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers. To communicate effectively through Twitter, policy makers need to understand how influence and interest propagate within its network of users. In this chapter we use graph-theoretic methods to analyse the Twitter debate surrounding NHS Englands controversial care.data scheme. Directionality is a crucial feature of the Twitter social graph - information flows from the followed to the followers - but is often ignored in social network analyses; our methods are based on the behaviour of dynamic processes on the network and can be applied naturally to directed networks. We uncover robust communities of users and show that these communities reflect how information flows through the Twitter network. We are also able to classify users by their differing roles in directing the flow of information through the network. Our methods and results will be useful to policy makers who would like to use Twitter effectively as a communication medium

Threats to safe transitions from hospital to home: a consensus study in North West London primary care.

BACKGROUND: Transitions between healthcare settings are vulnerable points for patients. AIM: To identify key threats to safe patient transitions from hospital to primary care settings. DESIGN AND SETTING: Three-round web-based Delphi consensus process among clinical and non-clinical staff from 39 primary care practices in North West London, England. METHOD: Round 1 was a free-text idea-generating round. Rounds 2 and 3 were consensus-obtaining rating rounds. Practices were encouraged to complete the questionnaires at team meetings. Aggregate ratings of perceived level of importance for each threat were calculated (1-3: 'not important', 4-6: 'somewhat important', 7-9: 'very important'). Percentage of votes cast for each patient or medication group were recorded; consensus was defined as ≥75%. RESULTS: A total of 39 practices completed round 1, 36/39 (92%) completed round 2, and 30/36 (83%) completed round 3. Round 1 identified nine threats encompassing problems involving communication, service organisation, medication provision, and patients who were most at risk. 'Poor quality of handover instructions from secondary to primary care teams' achieved the highest rating (mean rating at round 3 = 8.43) and a 100% consensus that it was a 'very important' threat. Older individuals (97%) and patients with complex medical problems taking >5 medications (80%) were voted the most vulnerable. Anticoagulants (77%) were considered to pose the greatest risk to patients. CONCLUSION: This study identified specific threats to safe patient transitions from hospital to primary care, providing policymakers and healthcare providers with targets for quality improvement strategies. Further work would need to identify factors underpinning these threats so that interventions can be tailored to the relevant behavioural and environmental contexts in which these threats arise

A Patient-Centered Framework for Evaluating Digital Maturity of Health Services: A Systematic Review

© Kelsey Flott, Ryan Callahan, Ara Darzi, Erik Mayer.Background: Digital maturity is the extent to which digital technologies are used as enablers to deliver a high-quality health service. Extensive literature exists about how to assess the components of digital maturity, but it has not been used to design a comprehensive framework for evaluation. Consequently, the measurement systems that do exist are limited to evaluating digital programs within one service or care setting, meaning that digital maturity evaluation is not accounting for the needs of patients across their care pathways. Objective: The objective of our study was to identify the best methods and metrics for evaluating digital maturity and to create a novel, evidence-based tool for evaluating digital maturity across patient care pathways. Methods: We systematically reviewed the literature to find the best methods and metrics for evaluating digital maturity. We searched the PubMed database for all papers relevant to digital maturity evaluation. Papers were selected if they provided insight into how to appraise digital systems within the health service and if they indicated the factors that constitute or facilitate digital maturity. Papers were analyzed to identify methodology for evaluating digital maturity and indicators of digitally mature systems. We then used the resulting information about methodology to design an evaluation framework. Following that, the indicators of digital maturity were extracted and grouped into increasing levels of maturity and operationalized as metrics within the evaluation framework. Results: We identified 28 papers as relevant to evaluating digital maturity, from which we derived 5 themes. The first theme concerned general evaluation methodology for constructing the framework (7 papers). The following 4 themes were the increasing levels of digital maturity: resources and ability (6 papers), usage (7 papers), interoperability (3 papers), and impact (5 papers). The framework includes metrics for each of these levels at each stage of the typical patient care pathway. Conclusions: The framework uses a patient-centric model that departs from traditional service-specific measurements and allows for novel insights into how digital programs benefit patients across the health system

Systematic review of hospital readmissions in stroke patients

Background Previous evidence on factors and causes of readmissions associated with high-impact users of stroke is scanty. The aim of the study was to investigate common causes and pattern of short- and long-term readmissions stroke patients by conducting a systematic review of studies using hospital administrative data. Common risk factors associated with the change of readmission rate were also examined. Methods The literature search was conducted from 15th February to 15th March 2016 using various databases, such as Medline, Embase, and Web of Science. Results There were total of 24 studies (n=2,126,617) included in the review. Only 4 studies assessed causes of readmissions in stroke patients with the follow-up duration from 30 days to 5 years. Common causes of readmissions in majority of the studies were recurrent stroke, infections and cardiac conditions. Common patient-related risk factors associated with increased readmission rate were age and history of coronary heart disease, heart failure, renal disease, respiratory disease, peripheral arterial disease and diabetes. Among stroke-related factors, length of stay of index stroke admission was associated with increased readmission rate, followed by bowel incontinence, feeding tube and urinary catheter. Conclusion Although risk factors and common causes of readmission were identified, but none of the previous studies investigated causes and their sequence of readmissions among high-impact stroke users