scholarly journals Automated identification of thoracic pathology from chest radiographs with enhanced training pipeline

2019 ◽  
Author(s):  
Adora M. DSouza ◽  
Anas Z. Abidin ◽  
Axel Wismüller
Keyword(s):  
Chest Radiographs ◽  
Automated Identification

Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration

2020 ◽  
Vol 30 (12) ◽  
pp. 6902-6912
Author(s):  
Eui Jin Hwang ◽  
Hyungjin Kim ◽  
Jong Hyuk Lee ◽  
Jin Mo Goo ◽  
Chang Min Park
Keyword(s):  
Deep Learning ◽  
Chest Radiographs ◽  
Automated Identification

A computerized method for automated identification of erect posteroanterior and supine anteroposterior chest radiographs

2011 ◽  
Vol 56 (24) ◽  
pp. 7737-7753 ◽  
Author(s):  
E-Fong Kao ◽  
Wei-Chen Lin ◽  
Jui-Sheng Hsu ◽  
Ming-Chung Chou ◽  
Twei-Shiun Jaw ◽  
...  
Keyword(s):  
Chest Radiographs ◽  
Automated Identification ◽  
Computerized Method

Analyzing Language in Suicide Notes and Legacy Tokens

Crisis ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 140-147 ◽  
Author(s):  
Michael J. Egnoto ◽  
Darrin J. Griffin
Keyword(s):  
Text Analysis ◽  
Low Cost ◽  
Computer Software ◽  
Student Writing ◽  
Computer Assisted ◽  
Automated Identification ◽  
Completed Suicide ◽  
Suicide Notes ◽  
Self Harm ◽  
Harm To Others

Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.

Radiographic Findings of Primary Lung Cancer with Delayed Detection on Chest Radiographs

1999 ◽  
Vol 40 (5) ◽  
pp. 879
Author(s):  
Young Min Kim ◽  
Jin Hwan Kim ◽  
Chang Kyu Yang ◽  
Bin Young Jung ◽  
Kwang Jin Jun ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Primary Lung Cancer ◽  
Chest Radiographs ◽  
Radiographic Findings

Assessment of Congestive Heart Failure in Chest Radiographs

1990 ◽  
Vol 31 (5) ◽  
pp. 469-471 ◽  
Author(s):  
L. Henriksson ◽  
A. Sundin ◽  
O. Smedby ◽  
P. Albrektsson
Keyword(s):  
Heart Failure ◽  
Congestive Heart Failure ◽  
Chest Radiographs
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