Utilization of smart devices and the evolution of customized healthcare services focusing on big data: a systematic review
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ABSTRACT:
SUBMITTER: Son Y
PROVIDER: S-EPMC10839508 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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Project description:The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing "big" data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having "big data" to create "smart data," with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.
| S-EPMC5511962 | biostudies-other
Project description:BackgroundThis article presents the Container Profiler, a software tool that measures and records the resource usage of any containerized task. Our tool profiles the CPU, memory, disk, and network utilization of containerized tasks collecting over 60 Linux operating system metrics at the virtual machine, container, and process levels. The Container Profiler supports performing time-series profiling at a configurable sampling interval to enable continuous monitoring of the resources consumed by containerized tasks and pipelines.ResultsTo investigate the utility of the Container Profiler, we profile the resource utilization requirements of a multistage bioinformatics analytical pipeline (RNA sequencing using unique molecular identifiers). We examine profiling metrics to assess patterns of CPU, disk, and network resource utilization across the different stages of the pipeline. We also quantify the profiling overhead of our Container Profiler tool to assess the impact of profiling a running pipeline with different levels of profiling granularity, verifying that impacts are negligible.ConclusionsThe Container Profiler provides a useful tool that can be used to continuously monitor the resource consumption of long and complex containerized applications that run locally or on the cloud. This can help identify bottlenecks where more resources are needed to improve performance.
| S-EPMC10452954 | biostudies-literature
Project description:Recently, the rapid development of the Internet of Things (IoT) has led to an increasing exponential growth of non-scalar data (e.g., images, videos). Local services are far from satisfying storage requirements, and the cloud computing fails to effectively support heterogeneous distributed IoT environments, such as wireless sensor network. To effectively provide smart privacy protection for video data storage, we take full advantage of three patterns (multi-access edge computing, cloudlets and fog computing) of edge computing to design the hierarchical edge computing architecture, and propose a low-complexity and high-secure scheme based on it. The video is divided into three parts and stored in completely different facilities. Specifically, the most significant bits of key frames are directly stored in local sensor devices while the least significant bits of key frames are encrypted and sent to the semi-trusted cloudlets. The non-key frame is compressed with the two-layer parallel compressive sensing and encrypted by the 2D logistic-skew tent map and then transmitted to the cloud. Simulation experiments and theoretical analysis demonstrate that our proposed scheme can not only provide smart privacy protection for big video data storage based on the hierarchical edge computing, but also avoid increasing additional computation burden and storage pressure.
| S-EPMC7085714 | biostudies-literature
Project description:The increasingly wide usage of smart infrastructure and location-aware terminals has helped increase the availability of trajectory data with rich spatiotemporal information. The development of data mining and analysis methods has allowed researchers to use these trajectory datasets to identify urban reality (e.g., citizens' collective behavior) in order to solve urban problems in transportation, environment, public security, etc. However, existing studies in this field have been relatively isolated, and an integrated and comprehensive review is lacking the problems that have been tackled, methods that have been tested, and services that have been generated from existing research. In this paper, we first discuss the relationships among the prevailing trajectory mining methods and then, classify the applications of trajectory data into three major groups: social dynamics, traffic dynamics, and operational dynamics. Finally, we briefly discuss the services that can be developed from studies in this field. Practical implications are also delivered for participants in trajectory data mining. With a focus on relevance and association, our review is aimed at inspiring researchers to identify gaps among tested methods and guiding data analysts and planners to select the most suitable methods for specific problems.
| S-EPMC7472055 | biostudies-literature
Project description:Advancements in genomics and personalized medicine not only effect healthcare delivery from patient and provider standpoints, but also reshape biomedical discovery. We are in the era of the '-omics', wherein an individual's genome, transcriptome, proteome and metabolome can be scrutinized to the finest resolution to paint a personalized biochemical fingerprint that enables tailored treatments, prognoses, risk factors, etc. Digitization of this information parlays into 'big data' informatics-driven evidence-based medical practice. While individualized patient management is a key beneficiary of next-generation medical informatics, this data also harbors a wealth of novel therapeutic discoveries waiting to be uncovered. 'Big data' informatics allows for networks-driven systems pharmacodynamics whereby drug information can be coupled to cellular- and organ-level physiology for determining whole-body outcomes. Patient '-omics' data can be integrated for ontology-based data-mining for the discovery of new biological associations and drug targets. Here we highlight the potential of 'big data' informatics for clinical pharmacology.
| S-EPMC4448933 | biostudies-other
Project description:BACKGROUND:The number of Chinese migrants in Sub-Saharan Africa (SSA) is increasing, which is part of the south-south migration. The healthcare seeking challenges for Chinese migrants in Africa are different from local people and other global migrants. The aim of this study is to explore utilization of local health services and barriers to health services access among Chinese migrants in Kenya. METHODS:Thirteen in-depth interviews (IDIs) and six focus group discussions (FGDs) were conducted among Chinese migrants (n?=?32) and healthcare-related stakeholders (n?=?3) in Nairobi and Kisumu, Kenya. Data was collected, transcribed, translated, and analyzed for themes. RESULTS:Chinese migrants in Kenya preferred self-treatment by taking medicines from China. When ailments did not improve, they then sought care at clinics providing Traditional Chinese Medicine (TCM) or received treatment at Kenyan private healthcare facilities. Returning to China for care was also an option depending on the perceived severity of disease. The main supply-side barriers to local healthcare utilization by Chinese migrants were language and lack of health insurance. The main demand-side barriers included ignorance of available healthcare services and distrust of local medical care. CONCLUSIONS:Providing information on quality healthcare services in Kenya, which includes Chinese language translation assistance, may improve utilization of local healthcare facilities by Chinese migrants in the country.
| S-EPMC6933712 | biostudies-literature
Project description:BackgroundPsychological distress among young people is increasing in Northern Europe. According to established healthcare utilization theory, this will create a greater need for youth primary healthcare and subsequently lead to more help-seeking behavior by distressed young people. The aim of this study was to investigate the association between the use of youth primary healthcare services and psychological distress in times of increasing mental health problems and increased service need.MethodsThis study consisted of five waves of repeated annual cross-sectional data collected from young people (aged 13-19) living in Norway between 2014 and 2018 (n = 368,579). Population-weighted and design-adjusted generalized linear regression with a log-link was used to examine the use of youth primary healthcare services over time.ResultsWe found that a large proportion of young people use primary healthcare services and that young people with high levels of psychological distress use primary healthcare services twice as much as their peers with low levels of psychological distress. In addition, between 2014 and 2018 both psychological distress and primary healthcare service utilization increased: psychological distress increased by 5% and total primary healthcare service use increased by 500 consultations per 1000 young people. Overall, psychological distress had a conditional association with youth primary healthcare service use and could account for between 16 and 66% of the change in the use of services between 2014 and 2018, depending on the service type. However, the absolute increase seen in the use of primary healthcare services was mainly driven by young people with low levels of psychological distress as opposed to young people with high psychological distress. This suggest a converging trend.ConclusionsOur findings suggest that there might be serious barriers between need and help-seeking behavior for young people with high levels of psychological distress and that the pattern of utilization among young people with lower distress may indicate overuse, possibly as an inadvertent consequence of a newly introduced school absence policy. While further research is needed to confirm these findings, our work may inform healthcare providers and policy makers about primary healthcare utilization trends among young people.
| S-EPMC7860003 | biostudies-literature
Project description: Not available
| S-EPMC6297460 | biostudies-literature
Project description:Primary outcome(s): change of stress data from start to stop of treatment or 12 weeks after, whichever comes first
| 2724817 | ecrin-mdr-crc
Project description:ObjectivesEnsuring access to care for all patients-especially those with life-threatening and chronic conditions-during a pandemic is a challenge for all healthcare systems. During the COVID-19 pandemic, many countries faced excess mortality partly attributed to disruptions in essential healthcare services provision. This study aims to estimate the utilization of public primary care and hospital services during the COVID-19 epidemic in Greece and its potential association with excess non-COVID-19 mortality in the country.Study designThis is an observational study.MethodsA retrospective analysis of national secondary utilization and mortality data from multiple official sources, covering the first nine months of the COVID-19 epidemic in Greece (February 26th to November 30th, 2020), was carried out.ResultsUtilization rates of all public healthcare services during the first nine months of the epidemic dropped significantly compared to the average utilization rates of the 2017-19 control period; hospital admissions, hospital surgical procedures, and primary care visits dropped by 17.3% (95% CI: 6.6%-28.0%), 23.1% (95% CI: 7.3%-38.9%), and 24.8% (95% CI: 13.3%-36.3%) respectively. This underutilization of essential public services-mainly due to supply restrictions such as suspension of outpatient care and cancelation of elective surgeries-is most probably related to the 3778 excess non-COVID-19 deaths (representing 62% of all-cause excess deaths) that have been reported during the first 9 months of the epidemic in the country.ConclusionsGreece's healthcare system, deeply wounded by the 2008-18 recession and austerity, was ill-resourced to cope with the challenges of the COVID-19 epidemic. Early and prolonged lockdowns have kept COVID-19 infections and deaths at relatively low levels. However, this "success" seems to have been accomplished at the expense of non-COVID-19 patients. It is important to acknowledge the "hidden epidemic" of unmet non-COVID-19 needs and increased non-COVID-19 deaths in the country and urgently strengthen public healthcare services to address it.
| S-EPMC9451614 | biostudies-literature