ENTEROGASTRIC REFLUX MIMICKING GALLBLADDER DISEASE: DETECTION, QUANTITATION AND POTENTIAL SIGNIFICANCE

1997 ◽  
Vol 22 (8) ◽  
pp. 577
Author(s):  
A. Arroyo ◽  
B. Burns ◽  
P. Patel
Keyword(s):  
Gallbladder Disease ◽  
Disease Detection ◽  
Potential Significance ◽  
Enterogastric Reflux

Enterogastric Reflux: an Uncommon Diagnosis Analyzed by Hepatobiliary Imaging

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Peter Wang
Keyword(s):  
Abdominal Pain ◽  
Digestive Enzymes ◽  
Gallbladder Disease ◽  
Hepatobiliary Scintigraphy ◽  
Hepatobiliary Imaging ◽  
Upper Gi ◽  
Gi Symptoms ◽  
Upper Abdominal ◽  
Enterogastric Reflux

Enterogastric reflux (EGR) is the reflux of bile and digestive enzymes from the small bowel into the stomach. While it is a normal physiologic process in small amounts, excessive reflux and chronic EGR can cause upper GI symptoms often mimicking more common diseases such as gallbladder disease and GERD that often leads to its underdiagnosis. Identifying EGR is significant as it has been associated with the development of gastroesophogeal pathology including gastritis, esophagitis, ulcers, and mucosal metaplasia. This article presents a 22-year-old male with enterogastric reflux causing upper abdominal pain and will discuss the role of hepatobiliary scintigraphy in its diagnosis.

Enterogastric Reflux: An Uncommon Diagnosis Analyzed by Hepatobiliary Imaging

2019 ◽  
Vol 8 (3) ◽  
Author(s):  
Peter Wang
Keyword(s):  
Abdominal Pain ◽  
Digestive Enzymes ◽  
Gallbladder Disease ◽  
Hepatobiliary Scintigraphy ◽  
Hepatobiliary Imaging ◽  
Upper Gi ◽  
Gi Symptoms ◽  
Upper Abdominal ◽  
Enterogastric Reflux

Enterogastric reflux (EGR) is the reflux of bile and digestive enzymes from the small bowel into the stomach. While it is a normal physiologic process in small amounts, excessive reflux and chronic EGR can cause upper GI symptoms often mimicking more common diseases such as gallbladder disease and GERD that often leads to its underdiagnosis. Identifying EGR is significant as it has been associated with the development of gastroesophogeal pathology including gastritis, esophagitis, ulcers, and mucosal metaplasia. This article presents a 22-year-old male with enterogastric reflux causing upper abdominal pain and will discuss the role of hepatobiliary scintigraphy in its diagnosis.

Visual Evoked-Response Correlates of Speechreading Performance in Normal-Hearing Adults

1983 ◽  
Vol 26 (1) ◽  
pp. 2-9 ◽  
Author(s):  
Vincent J. Samar ◽  
Donald G. Sims
Keyword(s):  
Multiple Correlation Coefficient ◽  
Evoked Response ◽  
Multiple Correlation ◽  
Potential Significance ◽  
Visual Evoked Response ◽  
Latency Measure ◽  
Two Measures ◽  
Components Analysis ◽  
The Relationship ◽  
Visual Evoked

The relationship between the latency of the negative peak occurring at approximately 130 msec in the visual evoked-response (VER) and speechreading scores was investigated. A significant product-moment correlation of -.58 was obtained between the two measures, which confirmed the fundamental effect but was significantly weaker than that previously reported in the literature (-.90). Principal components analysis of the visual evoked-response waveforms revealed a previously undiscovered early VER component, statistically independent of the latency measure, which in combination with two other components predicted speechreading with a multiple correlation coefficient of S4. The potential significance of this new component for the study of individual differences in speechreading ability is discussed.

Incidence and Prevalence of Bile Duct and Gallbladder Disease in Patients with Diabetes in the U.S.

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1559-P
Author(s):  
AYAD K. ALI ◽  
OMOLARA R. ADETUNJI
Keyword(s):  
Bile Duct ◽  
Gallbladder Disease ◽  
Patients With Diabetes ◽  
The U.S

A Review on Heart Disease Detection Techniques

2017 ◽  
Vol 7 (7) ◽  
pp. 395
Author(s):  
. Anika ◽  
Navpreet Kaur
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Review Paper ◽  
Vascular Diseases ◽  
Disease Detection ◽  
Automated Classification ◽  
Feature Extraction Method ◽  
Detection Techniques ◽  
Cardio Vascular ◽  
Public Domain Software

The paper exhibits a formal audit on early detection of heart disease which are the major cause of death. Computational science has potential to detect disease in prior stages automatically. With this review paper we describe machine learning for disease detection. Machine learning is a method of data analysis that automates analytical model building.Various techniques develop to predict cardiac disease based on cases through MRI was developed. Automated classification using machine learning. Feature extraction method using Cell Profiler and GLCM. Cell Profiler a public domain software, freely available is flourished by the Broad Institute's Imaging Platform and Glcm is a statistical method of examining texture .Various techniques to detect cardio vascular diseases.

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