Anesthesia decision analysis using a cloud-based big data platform
© 2024. The Author(s)..
Big data technologies have proliferated since the dawn of the cloud-computing era. Traditional data storage, extraction, transformation, and analysis technologies have thus become unsuitable for the large volume, diversity, high processing speed, and low value density of big data in medical strategies, which require the development of novel big data application technologies. In this regard, we investigated the most recent big data platform breakthroughs in anesthesiology and designed an anesthesia decision model based on a cloud system for storing and analyzing massive amounts of data from anesthetic records. The presented Anesthesia Decision Analysis Platform performs distributed computing on medical records via several programming tools, and provides services such as keyword search, data filtering, and basic statistics to reduce inaccurate and subjective judgments by decision-makers. Importantly, it can potentially to improve anesthetic strategy and create individualized anesthesia decisions, lowering the likelihood of perioperative complications.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:29 |
|---|---|
| Enthalten in: |
European journal of medical research - 29(2024), 1 vom: 25. März, Seite 201 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Zhang, Shuiting [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Anesthesia analysis |
|---|
| Anmerkungen: |
Date Completed 27.03.2024 Date Revised 26.04.2024 published: Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1186/s40001-024-01764-0 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM370181239 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM370181239 | ||
| 003 | DE-627 | ||
| 005 | 20240426234013.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240327s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1186/s40001-024-01764-0 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1388.xml |
| 035 | |a (DE-627)NLM370181239 | ||
| 035 | |a (NLM)38528564 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Zhang, Shuiting |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Anesthesia decision analysis using a cloud-based big data platform |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 27.03.2024 | ||
| 500 | |a Date Revised 26.04.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2024. The Author(s). | ||
| 520 | |a Big data technologies have proliferated since the dawn of the cloud-computing era. Traditional data storage, extraction, transformation, and analysis technologies have thus become unsuitable for the large volume, diversity, high processing speed, and low value density of big data in medical strategies, which require the development of novel big data application technologies. In this regard, we investigated the most recent big data platform breakthroughs in anesthesiology and designed an anesthesia decision model based on a cloud system for storing and analyzing massive amounts of data from anesthetic records. The presented Anesthesia Decision Analysis Platform performs distributed computing on medical records via several programming tools, and provides services such as keyword search, data filtering, and basic statistics to reduce inaccurate and subjective judgments by decision-makers. Importantly, it can potentially to improve anesthetic strategy and create individualized anesthesia decisions, lowering the likelihood of perioperative complications | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a Anesthesia analysis | |
| 650 | 4 | |a Big data | |
| 650 | 4 | |a Cloud-based | |
| 650 | 4 | |a Decision-making | |
| 650 | 4 | |a Platform | |
| 650 | 4 | |a Precision medicine | |
| 650 | 7 | |a Anesthetics |2 NLM | |
| 700 | 1 | |a Li, Hui |e verfasserin |4 aut | |
| 700 | 1 | |a Jing, Qiancheng |e verfasserin |4 aut | |
| 700 | 1 | |a Shen, Weiyun |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Wei |e verfasserin |4 aut | |
| 700 | 1 | |a Dai, Ruping |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t European journal of medical research |d 1998 |g 29(2024), 1 vom: 25. März, Seite 201 |w (DE-627)NLM090122402 |x 2047-783X |7 nnns |
| 773 | 1 | 8 | |g volume:29 |g year:2024 |g number:1 |g day:25 |g month:03 |g pages:201 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1186/s40001-024-01764-0 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 29 |j 2024 |e 1 |b 25 |c 03 |h 201 | ||