Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources.
about
Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.Integrating Natural Language Processing and Machine Learning Algorithms to Categorize Oncologic Response in Radiology Reports.Evaluation of Clinical Text Segmentation to Facilitate Cohort Retrieval.Building interpretable models for polypharmacy prediction in older chronic patients based on drug prescription records
P2860
Text mining electronic hospital records to automatically classify admissions against disease: Measuring the impact of linking data sources.
description
2016 nî lūn-bûn
@nan
2016 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2016 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
name
Text mining electronic hospita ...... mpact of linking data sources.
@ast
Text mining electronic hospita ...... mpact of linking data sources.
@en
type
label
Text mining electronic hospita ...... mpact of linking data sources.
@ast
Text mining electronic hospita ...... mpact of linking data sources.
@en
prefLabel
Text mining electronic hospita ...... mpact of linking data sources.
@ast
Text mining electronic hospita ...... mpact of linking data sources.
@en
P2093
P1476
Text mining electronic hospita ...... mpact of linking data sources.
@en
P2093
Chris Mac Manus
Christopher Bain
David Martinez
Gholamreza Haffari
Lawrence Cavedon
Simon Kocbek
P304
P356
10.1016/J.JBI.2016.10.008
P577
2016-10-11T00:00:00Z