Nothing
.onAttach <- function(libname, pkgname) {
options(future.globals = TRUE)
options(future.globals.maxSize = +Inf)
options(future.chunk.size = 1.0)
progressr::handlers(progressr::handler_progress(
format = ":spin [:bar] :percent in :elapsed ETA: :eta",
complete = "="
))
data.table::setDTthreads(threads = 1, restore_after_fork = FALSE)
packageStartupMessage("
_/_/_/ _/_/_/ _/_/_/ _/_/_/
_/_/_/ _/_/_/ _/ _/_/ _/_/_/ _/_/ _/ _/ _/ _/ _/ _/ _/ _/
_/ _/ _/ _/ _/_/ _/_/ _/_/_/_/ _/_/_/ _/_/_/ _/ _/ _/_/_/
_/ _/ _/ _/ _/ _/_/ _/ _/ _/ _/ _/ _/ _/ _/
_/_/_/ _/_/_/ _/ _/_/_/ _/_/_/ _/ _/ _/ _/_/_/ _/ _/
_/
_/
by: M\U00E1rton Kolossv\U00E1ry, MD PhD
Please cite:
Kolossv\U00E1ry M et al.
Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.
Radiology. 2023;306(2):e221926.
DOI: 10.1148/radiol.221926
")
}
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