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Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics
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| Zeitschriftentitel: | Anesthesia & Analgesia |
|---|---|
| Personen und Körperschaften: | , , |
| In: | Anesthesia & Analgesia, 127, 2018, 5, S. 1139-1143 |
| Format: | E-Article |
| Sprache: | Englisch |
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Ovid Technologies (Wolters Kluwer Health)
|
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Hofer, Ira S. Halperin, Eran Cannesson, Maxime Hofer, Ira S. Halperin, Eran Cannesson, Maxime |
|---|---|
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Hofer, Ira S. Halperin, Eran Cannesson, Maxime |
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Hofer, Ira S. Halperin, Eran Cannesson, Maxime Anesthesia & Analgesia Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics Anesthesiology and Pain Medicine |
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hofer, ira s. |
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Hofer, Ira S. Halperin, Eran Cannesson, Maxime 0003-2999 Ovid Technologies (Wolters Kluwer Health) Anesthesiology and Pain Medicine http://dx.doi.org/10.1213/ane.0000000000003463 <jats:p>Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical care is hard to find. This article aims to address these issues by first defining and elucidating the term big data, exploring the ways in which modern medical data, both inside and outside the electronic medical record, meet the established definitions of big data. We then define the term smart data and discuss the transformations necessary to make big data into smart data. Finally, we examine the ways in which this transition from big to smart data will affect what we do in research, retrospective work, and ultimately patient care.</jats:p> Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics Anesthesia & Analgesia |
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| title |
Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
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Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
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Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
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Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
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Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
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opening the black box: understanding the science behind big data and predictive analytics |
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Anesthesiology and Pain Medicine |
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http://dx.doi.org/10.1213/ane.0000000000003463 |
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<jats:p>Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical care is hard to find. This article aims to address these issues by first defining and elucidating the term big data, exploring the ways in which modern medical data, both inside and outside the electronic medical record, meet the established definitions of big data. We then define the term smart data and discuss the transformations necessary to make big data into smart data. Finally, we examine the ways in which this transition from big to smart data will affect what we do in research, retrospective work, and ultimately patient care.</jats:p> |
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| description | <jats:p>Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical care is hard to find. This article aims to address these issues by first defining and elucidating the term big data, exploring the ways in which modern medical data, both inside and outside the electronic medical record, meet the established definitions of big data. We then define the term smart data and discuss the transformations necessary to make big data into smart data. Finally, we examine the ways in which this transition from big to smart data will affect what we do in research, retrospective work, and ultimately patient care.</jats:p> |
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| spelling | Hofer, Ira S. Halperin, Eran Cannesson, Maxime 0003-2999 Ovid Technologies (Wolters Kluwer Health) Anesthesiology and Pain Medicine http://dx.doi.org/10.1213/ane.0000000000003463 <jats:p>Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical care is hard to find. This article aims to address these issues by first defining and elucidating the term big data, exploring the ways in which modern medical data, both inside and outside the electronic medical record, meet the established definitions of big data. We then define the term smart data and discuss the transformations necessary to make big data into smart data. Finally, we examine the ways in which this transition from big to smart data will affect what we do in research, retrospective work, and ultimately patient care.</jats:p> Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics Anesthesia & Analgesia |
| spellingShingle | Hofer, Ira S., Halperin, Eran, Cannesson, Maxime, Anesthesia & Analgesia, Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics, Anesthesiology and Pain Medicine |
| title | Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
| title_full | Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
| title_fullStr | Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
| title_full_unstemmed | Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
| title_short | Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
| title_sort | opening the black box: understanding the science behind big data and predictive analytics |
| title_unstemmed | Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics |
| topic | Anesthesiology and Pain Medicine |
| url | http://dx.doi.org/10.1213/ane.0000000000003463 |