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Machine learning literature review

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Start reading List of all articles. The General Insurance Machine Learning in Reserving working party is an international group of over 40 actuaries, bringing together experts in this field from around the globe. The idea of the working party is to help move this forward, by identifying what the barriers are, communicating any benefits, and helping develop the research techniques in pragmatic ways. At the same time we understand the resource and time pressures that reserving actuaries are under and the aim is not to replace existing reserving methods per se, but to start the journey to understanding if and how machine learning may help us in our day to day work. Our intention is to develop and undertake our own research. To this end, we have a number of workstreams addressing different issues.
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A literature review on machine learning in supply chain management

Machine learning literature review
Machine learning literature review
Machine learning literature review
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Machine Learning in Orthopedics: A Literature Review

To browse Academia. Skip to main content. Log In Sign Up. Download Free PDF. Arrahman Adnani. Download PDF. A short summary of this paper.
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An open-source machine learning framework to carry out systematic reviews

Machine learning ML has attracted much attention with the hope that it could make use of large, routinely collected datasets and deliver accurate personalised prognosis. The aim of this systematic review is to identify and critically appraise the reporting and developing of ML models for predicting outcomes after stroke. We searched PubMed and Web of Science from to March , using previously published search filters for stroke, ML, and prediction models. We focused on structured clinical data, excluding image and text analysis. Eighteen studies were eligible for inclusion.
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March 2, feature. When scientists carry out research on a given topic, they often start by reviewing previous study findings. Conducting systematic literature reviews or meta-analyses can be very challenging and time consuming, as there are often huge amounts of research focusing on different topics, which may not always be relevant to a researcher's work. Researchers at Utrecht University have recently developed a machine learning framework that could significantly speed up this process, by automatically browsing through numerous past studies and compiling high quality literature reviews.
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4 comment    
Eric M.

25.04.2021 5:53:18 Eric M.:

As it stands, I could have taught a better course than this, and maybe some day Ill be so fortunate as to move writing studies in the right direction, towards the truth that older generation teachers are unwilling to accept: that good writing is empirical, and therefore can be learned.

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25.04.2021 7:08:22 Asher B.:

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26.04.2021 18:36:09 Julien G.:

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Jose C.

27.04.2021 20:12:15 Jose C.:

Love the essays you do, very deep and consistent with the course materials and main ideas.

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