scholarly journals Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images

2021 ◽  
Author(s):  
Ziping Liu ◽  
Richard Laforest ◽  
Joyce Mhlanga ◽  
Tyler J. Fraum ◽  
Malak Itani ◽  
...  
Keyword(s):  
Observer Study

scholarly journals Clinical Decision Support for Ovarian Carcinoma Subtype Classification: A Pilot Observer Study With Pathology Trainees

2019 ◽  
Vol 144 (7) ◽  
pp. 869-877 ◽  
Author(s):  
Marios A. Gavrielides ◽  
Meghan Miller ◽  
Ian S. Hagemann ◽  
Heba Abdelal ◽  
Zahra Alipour ◽  
...  
Keyword(s):  
Decision Support ◽  
Ovarian Carcinoma ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Subspecialty Training ◽  
Reference Standard ◽  
Observer Study ◽  
Subtype Classification ◽  
The Impact ◽  
Whole Slide Images

Context.— Clinical decision support (CDS) systems could assist less experienced pathologists with certain diagnostic tasks for which subspecialty training or extensive experience is typically needed. The effect of decision support on pathologist performance for such diagnostic tasks has not been examined. Objective.— To examine the impact of a CDS tool for the classification of ovarian carcinoma subtypes by pathology trainees in a pilot observer study using digital pathology. Design.— Histologic review on 90 whole slide images from 75 ovarian cancer patients was conducted by 6 pathology residents using: (1) unaided review of whole slide images, and (2) aided review, where in addition to whole slide images observers used a CDS tool that provided information about the presence of 8 histologic features important for subtype classification that were identified previously by an expert in gynecologic pathology. The reference standard of ovarian subtype consisted of majority consensus from a panel of 3 gynecologic pathology experts. Results.— Aided review improved pairwise concordance with the reference standard for 5 of 6 observers by 3.3% to 17.8% (for 2 observers, increase was statistically significant) and mean interobserver agreement by 9.2% (not statistically significant). Observers benefited the most when the CDS tool prompted them to look for missed histologic features that were definitive for a certain subtype. Observer performance varied widely across cases with unanimous and nonunanimous reference classification, supporting the need for balancing data sets in terms of case difficulty. Conclusions.— Findings showed the potential of CDS systems to close the knowledge gap between pathologists for complex diagnostic tasks.

Detection of pulmonary nodule growth with dose reduced chest tomosynthesis: a human observer study using simulated nodules

2016 ◽  
Author(s):  
Christina Söderman ◽  
Åse Johnsson ◽  
Jenny Vikgren ◽  
Rauni Rossi Norrlund ◽  
David Molnar ◽  
...  
Keyword(s):  
Pulmonary Nodule ◽  
Human Observer ◽  
Observer Study ◽  
Nodule Growth

Digital Breast Tomosynthesis: A Pilot Observer Study

2008 ◽  
Vol 190 (4) ◽  
pp. 865-869 ◽  
Author(s):  
Walter F. Good ◽  
Gordon S. Abrams ◽  
Victor J. Catullo ◽  
Denise M. Chough ◽  
Marie A. Ganott ◽  
...  
Keyword(s):  
Digital Breast Tomosynthesis ◽  
Breast Tomosynthesis ◽  
Observer Study

Comparison of 2D versus 3D mammography with screening cases: an observer study

2012 ◽  
Author(s):  
James Reza Fernandez ◽  
Ruchi Deshpande ◽  
Linda Hovanessian-Larsen ◽  
Brent Liu
Keyword(s):  
Observer Study

A participant-observer study of ergonomics in engineering design:

2000 ◽  
Vol 31 (1) ◽  
pp. 73-82 ◽  
Author(s):  
Catherine M Burns ◽  
Kim J Vicente
Keyword(s):  
Engineering Design ◽  
Observer Study ◽  
Participant Observer

Evaluation of bi-objective treatment planning for high-dose-rate prostate brachytherapy—A retrospective observer study

Brachytherapy ◽  
2019 ◽  
Vol 18 (3) ◽  
pp. 396-403 ◽  
Author(s):  
Stefanus C. Maree ◽  
Ngoc Hoang Luong ◽  
Ernst S. Kooreman ◽  
Niek van Wieringen ◽  
Arjan Bel ◽  
...  
Keyword(s):  
Dose Rate ◽  
Treatment Planning ◽  
High Dose Rate ◽  
High Dose ◽  
Prostate Brachytherapy ◽  
Observer Study
Sign in / Sign up

Export Citation Format

Share Document