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Health monitoring data mining

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https://www.readbyqxmd.com/read/28632895/genome-mining-reveals-high-incidence-of-putative-lipopeptide-biosynthesis-nrps-pks-clusters-containing-fatty-acyl-amp-ligase-genes-in-biofilm-forming-cyanobacteria
#1
Tomáš Galica, Pavel Hrouzek, Jan Mareš
Cyanobacterial lipopeptides exhibit antimicrobial and antifungal bioactivities with potential for use in pharmaceutical research. However, due to their haemolytic activity and cytotoxic effects against human cells, they may pose a health issue if produced in substantial amounts in the environment. In bacteria, lipopeptides can be synthesized via several well-evidenced mechanisms. In one of them, fatty acyl-AMP ligase (FAAL) initiates the biosynthesis by activation of a fatty acyl residue. We have performed a bioinformatic survey of the cyanobacterial genomic information available in the public databases for the presence of FAAL-containing non-ribosomal peptide synthetase/polyketide synthetase (NRPS/PKS) biosynthetic clusters, as a genetic basis for lipopeptide biosynthesis...
June 20, 2017: Journal of Phycology
https://www.readbyqxmd.com/read/28550999/process-mining-routinely-collected-electronic-health-records-to-define-real-life-clinical-pathways-during-chemotherapy
#2
Karl Baker, Elaine Dunwoodie, Richard G Jones, Alex Newsham, Owen Johnson, Christopher P Price, Jane Wolstenholme, Jose Leal, Patrick McGinley, Chris Twelves, Geoff Hall
BACKGROUND: There is growing interest in the use of routinely collected electronic health records to enhance service delivery and facilitate clinical research. It should be possible to detect and measure patterns of care and use the data to monitor improvements but there are methodological and data quality challenges. Driven by the desire to model the impact of a patient self-test blood count monitoring service in patients on chemotherapy, we aimed to (i) establish reproducible methods of process-mining electronic health records, (ii) use the outputs derived to define and quantify patient pathways during chemotherapy, and (iii) to gather robust data which is structured to be able to inform a cost-effectiveness decision model of home monitoring of neutropenic status during chemotherapy...
July 2017: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/28536089/smart-devices-for-older-adults-managing-chronic-disease-a-scoping-review
#3
REVIEW
Ben Yb Kim, Joon Lee
BACKGROUND: The emergence of smartphones and tablets featuring vastly advancing functionalities (eg, sensors, computing power, interactivity) has transformed the way mHealth interventions support chronic disease management for older adults. Baby boomers have begun to widely adopt smart devices and have expressed their desire to incorporate technologies into their chronic care. Although smart devices are actively used in research, little is known about the extent, characteristics, and range of smart device-based interventions...
May 23, 2017: JMIR MHealth and UHealth
https://www.readbyqxmd.com/read/28503788/indicators-of-inappropriate-tumour-marker-use-through-the-mining-of-electronic-health-records
#4
Massimo Gion, Giulia Cardinali, Chiara Trevisiol, Marco Zappa, Giulia Rainato, Aline S C Fabricio
RATIONALE, AIMS, AND OBJECTIVES: Although the issue of monitoring appropriateness of tumour markers (TMs) request in outpatients remains crucial, proper indicators are still demanding. The present study developed and explored indicators of inappropriate TM ordering in outpatients through the data mining of electronic health records (EHRs). METHODS: Carcinoembryonic antigen (CEA), alfa-fetoprotein (AFP), carbohydrate antigen (CA)125, CA15.3, CA19.9, and prostate-specific antigen (PSA) ordered in outpatients during a year were examined by mining EHRs of a Local Health Authority in Italy...
May 15, 2017: Journal of Evaluation in Clinical Practice
https://www.readbyqxmd.com/read/28445441/mining-productive-associated-periodic-frequent-patterns-in-body-sensor-data-for-smart-home-care
#5
Walaa N Ismail, Mohammad Mehedi Hassan
The understanding of various health-oriented vital sign data generated from body sensor networks (BSNs) and discovery of the associations between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where occupants' health status is continuously monitored remotely, it is essential to provide the required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach for mining the periodic patterns obtained from BSN data...
April 26, 2017: Sensors
https://www.readbyqxmd.com/read/28422699/hemorrhage-prediction-models-in-surgical-intensive-care-bedside-monitoring-data-adds-information-to-lab-values
#6
Marco De Pasquale, Travis Moss, Sergio Cerutti, James Calland, Douglas Lake, Randall Moorman, Manuela Ferrario
Hemorrhage is a frequent complication in surgery patients; its identification and management have received increasing attention as a target for quality improvement in patient care in the Intensive Care Unit (ICU). The purposes of this work were i) to find an early detection model for hemorrhage by exploring the range of data mining methods that are currently available, and ii) to compare prediction models utilizing continuously measured physiological data from bedside monitors to those using commonly obtained laboratory tests...
April 12, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28331566/person-centered-prediction-of-survival-in-population-based-screening-program-by-an-intelligent-clinical-decision-support-system
#7
Reza Safdari, Elham Maserat, Hamid Asadzadeh Aghdaei, Amir Hossein Javan Amoli, Hamid Mohaghegh Shalmani
AIM: To survey person centered survival rate in population based screening program by an intelligent clinical decision support system. BACKGROUND: Colorectal cancer is the most common malignancy and major cause of morbidity and mortality throughout the world. Colorectal cancer is the sixth leading cause of cancer death in Iran. In this survey, we used cosine similarity as data mining technique and intelligent system for estimating survival of at risk groups in the screening plan...
2017: Gastroenterology and Hepatology From Bed to Bench
https://www.readbyqxmd.com/read/28251276/lack-of-essential-information-in-spontaneous-reports-of-adverse-drug-reactions-in-catalonia-a-restraint-to-the-potentiality-for-signal-detection
#8
Lorraine Plessis, Ainhoa Gómez, Núria García, Gloria Cereza, Albert Figueras
PURPOSE: The aim of this study is to analyze the quality of the information contained in the adverse drug reactions (ADR) reports and to describe the magnitude and characteristics of the lacking information. METHODS: All reports of serious ADR received by the Catalan Center of Pharmacovigilance in 2014 were analyzed using the VigiGrade and a more clinical and qualitative approach. RESULTS: Up to 824 reports describing serious ADR were included in the study; of them, 503 (61...
March 1, 2017: European Journal of Clinical Pharmacology
https://www.readbyqxmd.com/read/28214992/data-mining-in-hiv-aids-surveillance-system-application-to-portuguese-data
#9
Alexandra Oliveira, Brígida Mónica Faria, A Rita Gaio, Luís Paulo Reis
The Human Immunodeficiency Virus (HIV) is an infectious agent that attacks the immune system cells. Without a strong immune system, the body becomes very susceptible to serious life threatening opportunistic diseases. In spite of the great progresses on medication and prevention over the last years, HIV infection continues to be a major global public health issue, having claimed more than 36 million lives over the last 35 years since the recognition of the disease. Monitoring, through registries, of HIV-AIDS cases is vital to assess general health care needs and to support long-term health-policy control planning...
April 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28174760/mining-discriminative-patterns-to-predict-health-status-for-cardiopulmonary-patients
#10
Qian Cheng, Jingbo Shang, Joshua Juen, Jiawei Han, Bruce Schatz
Smartphones are ubiquitous now, but it is still unclear what physiological functions they can monitor at clinical quality. Pulmonary function is a standard measure of health status for cardiopulmonary patients. We have shown that predictive models can accurately classify cardiopulmonary conditions from healthy status, as well as different severity levels within cardiopulmonary disease, the GOLD stages. Here we propose several universal models to monitor cardiopulmonary conditions, including DPClass, a novel learning approach we designed...
October 2016: ACM-BCB: ACM Conference on Bioinformatics, Computational Biology and Biomedicine
https://www.readbyqxmd.com/read/28162030/infodemiology-of-systemic-lupus-erythematous-using-google-trends
#11
M Radin, S Sciascia
Objective People affected by chronic rheumatic conditions, such as systemic lupus erythematosus (SLE), frequently rely on the Internet and search engines to look for terms related to their disease and its possible causes, symptoms and treatments. 'Infodemiology' and 'infoveillance' are two recent terms created to describe a new developing approach for public health, based on Big Data monitoring and data mining. In this study, we aim to investigate trends of Internet research linked to SLE and symptoms associated with the disease, applying a Big Data monitoring approach...
January 1, 2017: Lupus
https://www.readbyqxmd.com/read/28130773/identification-of-substandard-medicines-via-disproportionality-analysis-of-individual-case-safety-reports
#12
Zahra Anita Trippe, Bruno Brendani, Christoph Meier, David Lewis
INTRODUCTION: The distribution and use of substandard medicines (SSMs) is a public health concern worldwide. The detection of SSMs is currently limited to expensive large-scale assay techniques such as high-performance liquid chromatography (HPLC). Since 2013, the Pharmacovigilance Department at Novartis Pharma AG has been analyzing drug-associated adverse events related to 'product quality issues' with the aim of detecting defective medicines using spontaneous reporting. The method of identifying SSMs with spontaneous reporting was pioneered by the Monitoring Medicines project in 2011...
January 28, 2017: Drug Safety: An International Journal of Medical Toxicology and Drug Experience
https://www.readbyqxmd.com/read/28126387/research-and-application-of-a-hybrid-model-based-on-dynamic-fuzzy-synthetic-evaluation-for-establishing-air-quality-forecasting-and-early-warning-system-a-case-study-in-china
#13
Yunzhen Xu, Pei Du, Jianzhou Wang
As the atmospheric environment pollution has been becoming more and more serious in China, it is highly desirable to develop a scientific and effective early warning system that plays a great significant role in analyzing and monitoring air quality. However, establishing a robust early warning system for warning the public in advance and ameliorating air quality is not only an extremely challenging task but also a public concerned problem for human health. Most previous studies are focused on improving the prediction accuracy, which usually ignore the significance of uncertainty information and comprehensive evaluation concerning air pollutants...
April 2017: Environmental Pollution
https://www.readbyqxmd.com/read/28073737/using-real-time-social-media-technologies-to-monitor-levels-of-perceived-stress-and-emotional-state-in-college-students-a-web-based-questionnaire-study
#14
Sam Liu, Miaoqi Zhu, Dong Jin Yu, Alexander Rasin, Sean D Young
BACKGROUND: College can be stressful for many freshmen as they cope with a variety of stressors. Excess stress can negatively affect both psychological and physical health. Thus, there is a need to find innovative and cost-effective strategies to help identify students experiencing high levels of stress to receive appropriate treatment. Social media use has been rapidly growing, and recent studies have reported that data from these technologies can be used for public health surveillance...
January 10, 2017: JMIR Mental Health
https://www.readbyqxmd.com/read/27895924/urinary-arsenic-species-concentration-in-residents-living-near-abandoned-metal-mines-in-south-korea
#15
Jin-Yong Chung, Byoung-Gwon Kim, Byung-Kook Lee, Jai-Dong Moon, Joon Sakong, Man Joong Jeon, Jung-Duck Park, Byung-Sun Choi, Nam-Soo Kim, Seung-Do Yu, Jung-Wook Seo, Byeong-Jin Ye, Hyoun-Ju Lim, Young-Seoub Hong
BACKGROUND: Arsenic is a carcinogenic heavy metal that has a species-dependent health effects and abandoned metal mines are a source of significant arsenic exposure. Therefore, the aims of this study were to analyze urinary arsenic species and their concentration in residents living near abandoned metal mines and to monitor the environmental health effects of abandoned metal mines in Korea. METHODS: This study was performed in 2014 to assess urinary arsenic excretion patterns of residents living near abandoned metal mines in South Korea...
2016: Annals of Occupational and Environmental Medicine
https://www.readbyqxmd.com/read/27650473/pm-10-episodes-in-greece-local-sources-versus-long-range-transport-observations-and-model-simulations
#16
Vasileios N Matthaios, Athanasios G Triantafyllou, Petros Koutrakis
Periods of abnormally high concentrations of atmospheric pollutants, defined as air pollution episodes, can cause adverse health effects. Southern European countries experience high particulate matter (PM) levels originating from local and distant sources. In this study, we investigated the occurrence and nature of extreme PM10 (PM with an aerodynamic diameter ≤10 μm) pollution episodes in Greece. We examined PM10 concentration data from 18 monitoring stations located at five sites across the country: (1) an industrial area in northwestern Greece (Western Macedonia Lignite Area, WMLA), which includes sources such as lignite mining operations and lignite power plants that generate a high percentage of the energy in Greece; (2) the greater Athens area, the most populated area of the country; and (3) Thessaloniki, (4) Patra, and (5) Volos, three large cities in Greece...
2017: Journal of the Air & Waste Management Association
https://www.readbyqxmd.com/read/27549158/pedagogical-monitoring-as-a-tool-to-reduce-dropout-in-distance-learning-in-family-health
#17
Deborah de Castro E Lima Baesse, Alexandra Monteiro Grisolia, Ana Emilia Figueiredo de Oliveira
BACKGROUND: This paper presents the results of a study of the Monsys monitoring system, an educational support tool designed to prevent and control the dropout rate in a distance learning course in family health. Developed by UNA-SUS/UFMA, Monsys was created to enable data mining in the virtual learning environment known as Moodle. METHODS: This is an exploratory study using documentary and bibliographic research and analysis of the Monsys database. Two classes (2010 and 2011) were selected as research subjects, one with Monsys intervention and the other without...
August 22, 2016: BMC Medical Education
https://www.readbyqxmd.com/read/27517928/human-behavior-analysis-by-means-of-multimodal-context-mining
#18
Oresti Banos, Claudia Villalonga, Jaehun Bang, Taeho Hur, Donguk Kang, Sangbeom Park, Thien Huynh-The, Vui Le-Ba, Muhammad Bilal Amin, Muhammad Asif Razzaq, Wahajat Ali Khan, Choong Seon Hong, Sungyoung Lee
There is sufficient evidence proving the impact that negative lifestyle choices have on people's health and wellness. Changing unhealthy behaviours requires raising people's self-awareness and also providing healthcare experts with a thorough and continuous description of the user's conduct. Several monitoring techniques have been proposed in the past to track users' behaviour; however, these approaches are either subjective and prone to misreporting, such as questionnaires, or only focus on a specific component of context, such as activity counters...
2016: Sensors
https://www.readbyqxmd.com/read/27471222/unsupervised-detection-and-analysis-of-changes-in-everyday-physical-activity-data
#19
Gina Sprint, Diane J Cook, Maureen Schmitter-Edgecombe
Sensor-based time series data can be utilized to monitor changes in human behavior as a person makes a significant lifestyle change, such as progress toward a fitness goal. Recently, wearable sensors have increased in popularity as people aspire to be more conscientious of their physical health. Automatically detecting and tracking behavior changes from wearable sensor-collected physical activity data can provide a valuable monitoring and motivating tool. In this paper, we formalize the problem of unsupervised physical activity change detection and address the problem with our Physical Activity Change Detection (PACD) approach...
October 2016: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/27455108/applying-gis-and-machine-learning-methods-to-twitter-data-for-multiscale-surveillance-of-influenza
#20
Chris Allen, Ming-Hsiang Tsou, Anoshe Aslam, Anna Nagel, Jean-Mark Gawron
Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding the spatial and temporal dynamics of outbreaks. Twitter gives researchers and public health officials an opportunity to examine the spread of influenza in real-time and at multiple geographical scales. In this paper, we introduce an improved framework for monitoring influenza outbreaks using the social media platform Twitter. Relying upon techniques from geographic information science (GIS) and data mining, Twitter messages were collected, filtered, and analyzed for the thirty most populated cities in the United States during the 2013-2014 flu season...
2016: PloS One
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