The promise of big data for palliative and end-of-life care research

Morin, Lucas; Onwuteaka‐Philipsen, Bregje D.

doi:10.1177/02692163211048307

Cited by 11 publications

(6 citation statements)

References 20 publications

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“…These tools improve the handling of large databases, a fundamental requirement in the era of big data. 7,8 This is demonstrated in studies by Jay et al 45 and Yoon et al 94 Both analyzed a database with a sample of approximately 58,000 entries of patients/caregivers. We noticed the increased use of freeware applications such as Python and R in more recent studies (2019 onward).…”

Section: Discussionmentioning

confidence: 99%

“…8 Despite these challenges in natural language processing for palliative care research, there are many benefits in using this method for improving the efficiency and accuracy of research studies. Morin and Onwuteaka-Philipsen 7 recently described that in order to move the field of palliative and end-of-life care research ahead, better and more diverse information about health-related issues (including quality of life and patient-reported outcomes) as well as the social and economic context in which people live during the last phase of their lives are needed.…”

Section: Introductionmentioning

confidence: 99%

“…[4][5][6] In less than a decade, big data and artificial intelligence have significantly contributed to technological progress in multiple fields and may also show promise as a new emerging technology in palliative care research. [7][8][9] However, some challenges are faced in the use of natural language processing for palliative care research, including the inadequate capture of certain information, such as non-hospital and mortality data, patient experience information, and available familial/social support. 8 Despite these challenges in natural language processing for palliative care research, there are many benefits in using this method for improving the efficiency and accuracy of research studies.…”

Section: Introductionmentioning

confidence: 99%

“…computer sciences, machine learning, linguistics). 7 Text classification and text similarity models, part of the natural language processing method, can extend our ability to undertake corpus linguistics across very large corpora. 11 Text mining techniques 6 can help researchers find the most accurate interpretation of research results.…”

Section: Introductionmentioning

confidence: 99%

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The use of natural language processing in palliative care research: A scoping review

et al. 2022

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Background: Natural language processing has been increasingly used in palliative care research over the last 5 years for its versatility and accuracy. Aim: To evaluate and characterize natural language processing use in palliative care research, including the most commonly used natural language processing software and computational methods, data sources, trends in natural language processing use over time, and palliative care topics addressed. Design: A scoping review using the framework by Arksey and O’Malley and the updated recommendations proposed by Levac et al. was conducted. Sources: PubMed, Web of Science, Embase, Scopus, and IEEE Xplore databases were searched for palliative care studies that utilized natural language processing tools. Data on study characteristics and natural language processing instruments used were collected and relevant palliative care topics were identified. Results: 197 relevant references were identified. Of these, 82 were included after full-text review. Studies were published in 48 different journals from 2007 to 2022. The average sample size was 21,541 (median 435). Thirty-two different natural language processing software and 33 machine-learning methods were identified. Nine main sources for data processing and 15 main palliative care topics across the included studies were identified. The most frequent topic was mortality and prognosis prediction. We also identified a trend where natural language processing was frequently used in analyzing clinical serious illness conversations extracted from audio recordings. Conclusions: We found 82 papers on palliative care using natural language processing methods for a wide-range of topics and sources of data that could expand the use of this methodology. We encourage researchers to consider incorporating this cutting-edge research methodology in future studies to improve published palliative care data.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The use of natural language processing in palliative care research: A scoping review

et al. 2022

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“…In the process of constructing the metabolism grey prediction model, based on the evaluation results of the complex network active intrusion metabolism diffusion process [26], the state transition probability value of the complex network active intrusion metabolism in the diffusion process is calculated by means of probability reasoning [27,28]. The basic principle of time series prediction is based on the trend prediction principle.…”

Section: Construction Of the Metabolic Grey Prediction Modelmentioning

confidence: 99%

The Metabolism Grey Prediction Model Based on Big Data and Internet of Things Technology

Ren

Sun

Shan

et al. 2022

Wireless Communications and Mobile Computing

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In view of the uncertainty and diversity of the metabolic grey prediction model in the prediction process, resulting in poor prediction effect, a metabolic grey prediction model based on big data and Internet of things technology is constructed. Establish the aerobic metabolic process of human telecontrol and put forward the detection index of aerobic metabolic cycle function in human telecontrol; on this basis, use the metabolic grey prediction model analysis algorithm to determine the active intrusion intention of complex network, establish the intrusion intention attack behavior set function, establish the internal operation architecture under the technology of big data and Internet of things, and realize the construction of metabolic grey prediction model. The experimental results show that the constructed model can realize data prediction, with high confidence level and good effect.

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How many people will live and die with serious illness in Ireland to 2040? Estimated needs and costs using microsimulation

May,

Normand,

Smith

et al. 2024

The Journal of the Economics of Ageing

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The promise of big data for palliative and end-of-life care research

Cited by 11 publications

References 20 publications

The use of natural language processing in palliative care research: A scoping review

The use of natural language processing in palliative care research: A scoping review

The Metabolism Grey Prediction Model Based on Big Data and Internet of Things Technology

How many people will live and die with serious illness in Ireland to 2040? Estimated needs and costs using microsimulation

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