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F1000Research
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February 27, 2016
Advances in upper gastrointestinal endoscopy
David G Graham, Matthew R Banks
Diagnostics (Basel, Switzerland)
|
February 10, 2024
Latest Advances in Endoscopic Detection of Oesophageal and Gastric Neoplasia
William Waddingham, David G Graham, Matthew R Banks
Frontline Gastroenterology
|
July 12, 2021
Recent advances in the detection and management of early gastric cancer and its precursors
William Waddingham, Stella A V Nieuwenburg, Sean Carlson, et al.
Epigenomics
|
April 26, 2018
A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix
Shijie C Zheng, Amy P Webster, Danyue Dong, et al.
Gastroenterology Research and Practice
|
September 25, 2018
Machine Learning Creates a Simple Endoscopic Classification System that Improves Dysplasia Detection in Barrett's Oesophagus amongst Non-expert Endoscopists
Vinay Sehgal, Avi Rosenfeld, David G Graham, et al.
Clinics and Research in Hepatology and Gastroenterology
|
January 20, 2023
Development and validation of a multivariable risk factor questionnaire to detect oesophageal cancer in 2-week wait patients
Kai Man Alexander Ho, Avi Rosenfeld, Áine Hogan, et al.
Plos One
|
March 10, 2020
An optimised saliva collection method to produce high-yield, high-quality RNA for translational research
Roisin Sullivan, Susan Heavey, David G Graham, et al.
Gastrointestinal Endoscopy
|
October 7, 2018
Virtual chromoendoscopy by using optical enhancement improves the detection of Barrett's esophagus-associated neoplasia
Martin A Everson, Laurence B Lovat, David G Graham, et al.
Clinical Epigenetics
|
February 15, 2022
Novel epigenetic network biomarkers for early detection of esophageal cancer
Alok K Maity, Timothy C Stone, Vanessa Ward, et al.
The Lancet. Digital Health
|
March 6, 2020
Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach
Avi Rosenfeld, David G Graham, Sarah Jevons, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
F1000Research
|
February 27, 2016
Advances in upper gastrointestinal endoscopy
David G Graham, Matthew R Banks
Diagnostics (Basel, Switzerland)
|
February 10, 2024
Latest Advances in Endoscopic Detection of Oesophageal and Gastric Neoplasia
William Waddingham, David G Graham, Matthew R Banks
Frontline Gastroenterology
|
July 12, 2021
Recent advances in the detection and management of early gastric cancer and its precursors
William Waddingham, Stella A V Nieuwenburg, Sean Carlson, et al.
Epigenomics
|
April 26, 2018
A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix
Shijie C Zheng, Amy P Webster, Danyue Dong, et al.
Gastroenterology Research and Practice
|
September 25, 2018
Machine Learning Creates a Simple Endoscopic Classification System that Improves Dysplasia Detection in Barrett's Oesophagus amongst Non-expert Endoscopists
Vinay Sehgal, Avi Rosenfeld, David G Graham, et al.
Clinics and Research in Hepatology and Gastroenterology
|
January 20, 2023
Development and validation of a multivariable risk factor questionnaire to detect oesophageal cancer in 2-week wait patients
Kai Man Alexander Ho, Avi Rosenfeld, Áine Hogan, et al.
Plos One
|
March 10, 2020
An optimised saliva collection method to produce high-yield, high-quality RNA for translational research
Roisin Sullivan, Susan Heavey, David G Graham, et al.
Gastrointestinal Endoscopy
|
October 7, 2018
Virtual chromoendoscopy by using optical enhancement improves the detection of Barrett's esophagus-associated neoplasia
Martin A Everson, Laurence B Lovat, David G Graham, et al.
Clinical Epigenetics
|
February 15, 2022
Novel epigenetic network biomarkers for early detection of esophageal cancer
Alok K Maity, Timothy C Stone, Vanessa Ward, et al.
The Lancet. Digital Health
|
March 6, 2020
Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach
Avi Rosenfeld, David G Graham, Sarah Jevons, et al.
Page
of 1