journal
https://read.qxmd.com/read/31700248/a-data-driven-approach-to-predicting-septic-shock-in-the-intensive-care-unit
#1
JOURNAL ARTICLE
Christopher R Yee, Niven R Narain, Viatcheslav R Akmaev, Vijetha Vemulapalli
Early diagnosis of sepsis and septic shock has been unambiguously linked to lower mortality and better patient outcomes. Despite this, there is a strong unmet need for a reliable clinical tool that can be used for large-scale automated screening to identify high-risk patients. We addressed the following questions: Can a novel algorithm to identify patients at high risk of septic shock 24 hours before diagnosis be discovered using available clinical data? What are performance characteristics of this predictive algorithm? Can current metrics for evaluation of sepsis be improved using novel algorithm? Publicly available data from the intensive care unit setting was used to build septic shock and control patient cohorts...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/31666794/lep-a-statistical-method-integrating-individual-level-and-summary-level-data-of-the-same-trait-from-different-populations
#2
COMMENT
Mingwei Dai, Jin Liu, Can Yang
Statistical approaches for integrating multiple data sets in genome-wide association studies (GWASs) are increasingly important. Proper utilization of more relevant information is expected to improve statistical efficiency in the analysis. Among these approaches, LEP was proposed for joint analysis of individual-level data and summary-level data in the same population by leveraging pleiotropy. The key idea of LEP is to explore correlation of the association status among different data sets while accounting for the heterogeneity...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/31391780/a-genome-model-to-explain-major-features-of-neurodevelopmental-disorders-in-newborns
#3
JOURNAL ARTICLE
Bernard Friedenson
The purpose of this study was to test the hypothesis that infections are linked to chromosomal anomalies that cause neurodevelopmental disorders. In children with disorders in the development of their nervous systems, chromosome anomalies known to cause these disorders were compared with foreign DNAs, including known teratogens. Genes essential for neurons, lymphatic drainage, immunity, circulation, angiogenesis, cell barriers, structure, epigenetic and chromatin modifications were all found close together in polyfunctional clusters that were deleted or rearranged in neurodevelopmental disorders...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/31190853/mathematical-model-for-computer-assisted-modification-of-medication-dosing-rules
#4
JOURNAL ARTICLE
Michael Z Grabel, Benjamin L Vaughan, Judith W Dexheimer, Eric S Kirkendall
Objective: Medication dosing in pediatrics is complex and prone to errors that may lead to patient harm. To improve computer-assisted dosing, a mathematical model and algorithm were developed to optimize clinical decision support dosing rules and reduce spurious alerts. The objective was to evaluate the feasibility of using this algorithm to adjust dosing rules. Materials and methods: Incorporating historical ordering data, a mathematical model and algorithm were developed to automatically determine optimal dosing rule parameters...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/30911219/applying-supervised-machine-learning-to-identify-which-patient-characteristics-identify-the-highest-rates-of-mortality-post-interhospital-transfer
#5
JOURNAL ARTICLE
Andrew P Reimer, Nicholas K Schiltz, Vanessa P Ho, Elizabeth A Madigan, Siran M Koroukian
Objective: To demonstrate the usefulness of applying supervised machine-learning analyses to identify specific groups of patients that experience high levels of mortality post-interhospital transfer. Methods: This was a cross-sectional analysis of data from the Health Care Utilization Project 2013 National Inpatient Sample, that applied supervised machine-learning approaches that included (1) classification and regression tree to identify mutually exclusive groups of patients and their associated characteristics of those experiencing the highest levels of mortality and (2) random forest to identify the relative importance of each characteristic's contribution to post-transfer mortality...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/30886520/coalitional-game-theory-facilitates-identification-of-non-coding-variants-associated-with-autism
#6
JOURNAL ARTICLE
Min Woo Sun, Anika Gupta, Maya Varma, Kelley M Paskov, Jae-Yoon Jung, Nate T Stockham, Dennis P Wall
Studies on autism spectrum disorder (ASD) have amassed substantial evidence for the role of genetics in the disease's phenotypic manifestation. A large number of coding and non-coding variants with low penetrance likely act in a combinatorial manner to explain the variable forms of ASD. However, many of these combined interactions, both additive and epistatic, remain undefined. Coalitional game theory (CGT) is an approach that seeks to identify players (individual genetic variants or genes) who tend to improve the performance-association to a disease phenotype of interest-of any coalition (subset of co-occurring genetic variants) they join...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/30858710/can-your-phone-be-your-therapist-young-people-s-ethical-perspectives-on-the-use-of-fully-automated-conversational-agents-chatbots-in-mental-health-support
#7
JOURNAL ARTICLE
Kira Kretzschmar, Holly Tyroll, Gabriela Pavarini, Arianna Manzini, Ilina Singh
Over the last decade, there has been an explosion of digital interventions that aim to either supplement or replace face-to-face mental health services. More recently, a number of automated conversational agents have also been made available, which respond to users in ways that mirror a real-life interaction. What are the social and ethical concerns that arise from these advances? In this article, we discuss, from a young person's perspective, the strengths and limitations of using chatbots in mental health support...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/30675101/incorporating-observed-physiological-data-to-personalize-pediatric-vital-sign-alarm-thresholds
#8
JOURNAL ARTICLE
Sarah Poole, Nigam Shah
Bedside monitors are intended as a safety net in patient care, but their management in the inpatient setting is a significant patient safety concern. The low precision of vital sign alarm systems leads to clinical staff becoming desensitized to the sound of the alarm, a phenomenon known as alarm fatigue. Alarm fatigue has been shown to increase response time to alarms or result in alarms being ignored altogether and has negative consequences for patient safety. We present methods to establish personalized thresholds for heart rate and respiratory rate alarms...
2019: Biomedical Informatics Insights
https://read.qxmd.com/read/30573966/views-from-the-street-pilot-study-constraints-and-difficulties-of-using-photographs-in-research-of-a-complex-nature-such-as-homelessness
#9
JOURNAL ARTICLE
Asmae Doukani, Xingjie Wei, Bibi Kader, Fabien Soazandry, Becky Inkser
Homeless people experience a unique set of challenges leading to pervasive health and social problems. An increasing number of researchers have harnessed photographic data to gain a unique perspective of marginalised groups. The aim of the study is to explore the feasibility of using photographs in research to understand the complex environment experienced by homeless people, with a special interest in mental health. Individuals who frequently attend homeless facilities in London were sensitively approached and asked if they would be interested in taking part in the 'Views From the Street' pilot study...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/30450002/imitating-pathologist-based-assessment-with-interpretable-and-context-based-neural-network-modeling-of-histology-images
#10
JOURNAL ARTICLE
Arunima Srivastava, Chaitanya Kulkarni, Kun Huang, Anil Parwani, Parag Mallick, Raghu Machiraju
Convolutional neural networks (CNNs) have gained steady popularity as a tool to perform automatic classification of whole slide histology images. While CNNs have proven to be powerful classifiers in this context, they fail to explain this classification, as the network engineered features used for modeling and classification are ONLY interpretable by the CNNs themselves. This work aims at enhancing a traditional neural network model to perform histology image modeling, patient classification, and interpretation of the distinctive features identified by the network within the histology whole slide images (WSIs)...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/30302053/monte-carlo-simulations-demonstrate-algorithmic-interventions-over-time-reduce-hospitalisation-in-patients-with-schizophrenia-and-bipolar-disorder
#11
JOURNAL ARTICLE
Alissa Knight, Geoff A Jarrad, Geoff D Schrader, Jorg Strobel, Dennis Horton, Niranjan Bidargaddi
Non-adherence with pharmacologic treatment is associated with increased rates of relapse and rehospitalisation among patients with schizophrenia and bipolar disorder. To improve treatment response, remission, and recovery, research efforts are still needed to elucidate how to effectively map patient's response to medication treatment including both therapeutic and adverse effects, compliance, and satisfaction in the prodromal phase of illness (ie, the time period in between direct clinical consultation and relapse)...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/30158823/humanizing-digital-mental-health-through-social-media-centering-experiences-of-gang-involved-youth-exposed-to-high-rates-of-violence
#12
REVIEW
William R Frey
As the lives of young people expand further into digital spaces, our understandings of their expressions and language on social media become more consequential for providing individualized and applicable mental health resources. This holds true for young people exposed to high rates of community violence who may also lack access to health resources offline. Social media may provide insights into the impacts of community violence exposure on mental health. However, much of what is shared on social media contains localized language and context, which poses challenges regarding interpretation...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/30158822/natural-language-processing-of-social-media-as-screening-for-suicide-risk
#13
REVIEW
Glen Coppersmith, Ryan Leary, Patrick Crutchley, Alex Fine
Suicide is among the 10 most common causes of death, as assessed by the World Health Organization. For every death by suicide, an estimated 138 people's lives are meaningfully affected, and almost any other statistic around suicide deaths is equally alarming. The pervasiveness of social media-and the near-ubiquity of mobile devices used to access social media networks-offers new types of data for understanding the behavior of those who (attempt to) take their own lives and suggests new possibilities for preventive intervention...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/30013355/experiences-of-donating-personal-data-to-mental-health-research-an-explorative-anthropological-study
#14
JOURNAL ARTICLE
Joanna Sleigh
Technological developments, such as the advent of social networking sites, apps, and tracking 'cookies', enable the generation and collection of unprecedented quantities of rich personal and behavioural data, opening up a vast new resource for mental health research. Despite these non-traditional health-related data already forming a vital foundation of many new research avenues, little analysis has been done focusing on the experiences, motivations, and concerns of the individuals already engaged in data sharing and donation practices...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/30013354/tech-has-it-s-place
#15
JOURNAL ARTICLE
Telixia Inico
No abstract text is available yet for this article.
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/29887730/automating-installation-of-the-integrating-biology-and-the-bedside-i2b2-platform
#16
REVIEW
Kavishwar B Wagholikar, Michael Mendis, Pralav Dessai, Javier Sanz, Sindy Law, Micheal Gilson, Stephan Sanders, Mahesh Vangala, Douglas S Bell, Shawn N Murphy
Informatics for Integrating Biology and the Bedside (i2b2) is an open source clinical data analytics platform used at more than 150 institutions for querying patient data. An i2b2 installation (called hive) comprises several i2b2 cells that provide different functionalities. Given the complex architecture of i2b2 installation, creating a working installation of the platform is challenging for new users. This is despite the availability of extensive documentation for i2b2 and access to a large and active mailing list community of i2b2 users...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/29872307/a-method-for-deriving-quasi-healthy-cohorts-from-clinical-data
#17
JOURNAL ARTICLE
Satoshi Irino, Yukio Kurihara
We evaluated quasi-healthy cohorts (model cohorts), derived from clinical data, to determine how well they simulated control cohorts. Control cohorts comprised individuals extracted from a public checkup database in Japan, under the condition that their values for 3 basic laboratory tests fall within specific reference ranges (3Ts condition). Model cohorts comprised outpatients, extracted from a clinical database at a hospital, under the 3Ts condition or under the condition that their values for 4 laboratory tests fall within specific reference ranges (4Ts condition)...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/29636619/accommodating-grief-on-twitter-an-analysis-of-expressions-of-grief-among-gang-involved-youth-on-twitter-using-qualitative-analysis-and-natural-language-processing
#18
JOURNAL ARTICLE
Desmond Upton Patton, Jamie MacBeth, Sarita Schoenebeck, Katherine Shear, Kathleen McKeown
There is a dearth of research investigating youths' experience of grief and mourning after the death of close friends or family. Even less research has explored the question of how youth use social media sites to engage in the grieving process. This study employs qualitative analysis and natural language processing to examine tweets that follow 2 deaths. First, we conducted a close textual read on a sample of tweets by Gakirah Barnes, a gang-involved teenaged girl in Chicago, and members of her Twitter network, over a 19-day period in 2014 during which 2 significant deaths occurred: that of Raason "Lil B" Shaw and Gakirah's own death...
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/29623001/proceedings-from-the-digital-innovation-in-mental-health-conference-london-2017
#19
EDITORIAL
Becky Inkster
Aims and Scope: The conference aims were two-fold: (1) to explore how digital technology is implemented into personalized and/or group mental health interventions and (2) to promote digital equality through developing culturally sensitive ways of bringing technological innovation to disadvantaged groups. A broad scope of perspectives were welcomed and encouraged, from lived experience, academic, clinical, media, the arts, policy-making, tech innovation, and other perspectives.
2018: Biomedical Informatics Insights
https://read.qxmd.com/read/29242701/a-software-tool-for-the-annotation-of-embolic-events-in-echo-doppler-audio-signals
#20
JOURNAL ARTICLE
Paola Pierleoni, Lorenzo Maurizi, Lorenzo Palma, Alberto Belli, Simone Valenti, Alessandro Marroni
The use of precordial Doppler monitoring to prevent decompression sickness (DS) is well known by the scientific community as an important instrument for early diagnosis of DS. However, the timely and correct diagnosis of DS without assistance from diving medical specialists is unreliable. Thus, a common protocol for the manual annotation of echo Doppler signals and a tool for their automated recording and annotation are necessary. We have implemented original software for efficient bubble appearance annotation and proposed a unified annotation protocol...
2017: Biomedical Informatics Insights
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