Automated identification of extreme-risk events in clinical incident reports.
about
Clinical research informatics: a conceptual perspectiveUsing multiclass classification to automate the identification of patient safety incident reports by type and severity.Prioritization of free-text clinical documents: a novel use of a bayesian classifier.Technology, cognition and error.Using statistical text classification to identify health information technology incidents.Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level AccuracyStatistical classification of drug incidents due to look-alike sound-alike mix-ups.
P2860
Q28386227-E932283B-DBC3-43FA-B44F-AA495FD826E2Q30855617-BDFF7618-4BE6-4C04-AED3-856C4B93D5F8Q35537666-4FEE7BB6-95D8-4B8F-8B10-96BAC47C42EAQ35792931-D27A024C-F2BA-401F-94BA-5D69E8F8CB3BQ37129501-9C054D08-14F4-449E-A641-B7D55D1FF211Q37727680-3369E49F-4943-4113-B0C6-A9A35758D432Q51013279-905C648B-F668-425C-BB77-5CCF2FA8364E
P2860
Automated identification of extreme-risk events in clinical incident reports.
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
2012年论文
@zh
2012年论文
@zh-cn
name
Automated identification of extreme-risk events in clinical incident reports.
@ast
Automated identification of extreme-risk events in clinical incident reports.
@en
type
label
Automated identification of extreme-risk events in clinical incident reports.
@ast
Automated identification of extreme-risk events in clinical incident reports.
@en
prefLabel
Automated identification of extreme-risk events in clinical incident reports.
@ast
Automated identification of extreme-risk events in clinical incident reports.
@en
P2860
P1476
Automated identification of extreme-risk events in clinical incident reports
@en
P2093
Farah Magrabi
Mei-Sing Ong
P2860
P304
P356
10.1136/AMIAJNL-2011-000562
P577
2012-01-11T00:00:00Z