[HTML][HTML] Using radiomics-based machine learning to create targeted test sets to improve specific mammography reader cohort performance: A feasibility study
Mammography interpretation is challenging with high error rates. This study aims to reduce
the errors in mammography reading by mapping diagnostic errors against global …
the errors in mammography reading by mapping diagnostic errors against global …
[HTML][HTML] AI for interpreting screening mammograms: implications for missed cancer in double reading practices and challenging-to-locate lesions
Although the value of adding AI as a surrogate second reader in various scenarios has been
investigated, it is unknown whether implementing an AI tool within double reading practice …
investigated, it is unknown whether implementing an AI tool within double reading practice …
The influence of viewing time on visual diagnostic accuracy: Less is more
Background Understanding the factors that contribute to diagnostic errors is critical if we are
to correct or prevent them. Some scholars influenced by the default interventionist dual …
to correct or prevent them. Some scholars influenced by the default interventionist dual …
[HTML][HTML] Using global feedback to induce learning of gist of abnormality in mammograms
Extraction of global structural regularities provides general 'gist'of our everyday visual
environment as it does the gist of abnormality for medical experts reviewing medical images …
environment as it does the gist of abnormality for medical experts reviewing medical images …
[HTML][HTML] Global Radiomic Features from Mammography for Predicting Difficult-To-Interpret Normal Cases
This work aimed to investigate whether global radiomic features (GRFs) from mammograms
can predict difficult-to-interpret normal cases (NCs). Assessments from 537 readers …
can predict difficult-to-interpret normal cases (NCs). Assessments from 537 readers …
[HTML][HTML] Spotting lesions in thorax X-rays at a glance: holistic processing in radiology
M Bilalić, T Grottenthaler, T Nägele, T Lindig - … Research: Principles and …, 2022 - Springer
Radiologists often need only a glance to grasp the essence of complex medical images.
Here, we use paradigms and manipulations from perceptual learning and expertise fields to …
Here, we use paradigms and manipulations from perceptual learning and expertise fields to …
[HTML][HTML] Multiple expressions of “expert” abnormality gist in novices following perceptual learning
GJ DiGirolamo, M DiDominica, MAJ Qadri… - … research: principles and …, 2023 - Springer
With a brief half-second presentation, a medical expert can determine at above chance
levels whether a medical scan she sees is abnormal based on a first impression arising from …
levels whether a medical scan she sees is abnormal based on a first impression arising from …
[HTML][HTML] Reliability of radiologists' first impression when interpreting a screening mammogram
Previous studies showed that radiologists can detect the gist of an abnormality in a
mammogram based on a half-second image presentation through global processing of …
mammogram based on a half-second image presentation through global processing of …
Predicting the gist of breast cancer on a screening mammogram using global radiomic features
S Siviengphanom, SJ Lewis… - Medical Imaging …, 2024 - spiedigitallibrary.org
This study explored if using a set of global radiomic (ie, computer-extracted) features derived
from mammograms could predict the gist of breast cancer (holistic perceptual information …
from mammograms could predict the gist of breast cancer (holistic perceptual information …
Multiple expressions of
GJ DiGirolamo, M DiDominica… - Cognitive …, 2023 - repository.escholarship.umassmed …
With a brief half-second presentation, a medical expert can determine at above chance
levels whether a medical scan she sees is abnormal based on a first impression arising from …
levels whether a medical scan she sees is abnormal based on a first impression arising from …