A data set to predict a binary outcome using imaging and patient data.
a tibble
These data were gathered to predict patient risk for ischemic stroke. A historical set of patients with a range of carotid artery blockages were selected. The data consisted of 126 patients, 44 of which had blockages greater than 70%. All patients had undergone Computed Tomography Angiography (CTA) to generate a detailed three-dimensional visualization and characterization of the blockage. These images were then analyzed in order to compute several features related to the disease, including: percent stenosis, arterial wall thickness, and tissue characteristics such as lipid-rich necrotic core and calcification.
The group of patients in this study also had follow-up information on whether or not a stroke occurred at a subsequent point in time. The data for each patient also included commonly collected clinical characteristics for risk of stroke such as whether or not the patient had atrial fibrillation, coronary artery disease, and a history of smoking. Demographics of gender and age were included as well. These readily available risk factors can be thought of as another potentially useful predictor set that can be evaluated. In fact, this set of predictors should be evaluated first to assess their ability to predict stroke since these predictors are easy to collect, are acquired at patient presentation, and do not require an expensive imaging technique.
Columns:
stroke
: factor (levels: 'yes' and 'no')
nascet_scale
: numeric
calc_vol
: numeric
calc_vol_prop
: numeric
matx_vol
: numeric
matx_vol_prop
: numeric
lrnc_vol
: numeric
lrnc_vol_prop
: numeric
max_calc_area
: numeric
max_calc_area_prop
: numeric
max_dilation_by_area
: numeric
max_matx_area
: numeric
max_matx_area_prop
: numeric
max_lrnc_area
: numeric
max_lrnc_area_prop
: numeric
max_max_wall_thickness
: numeric
max_remodeling_ratio
: numeric
max_stenosis_by_area
: numeric
max_wall_area
: numeric
wall_vol
: numeric
max_stenosis_by_diameter
: numeric
age
: integer
male
: integer
smoking_history
: integer
atrial_fibrillation
: integer
coronary_artery_disease
: integer
diabetes_history
: integer
hypercholesterolemia_history
: integer
hypertension_history
: integer
data(ischemic_stroke)
str(ischemic_stroke)
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