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Machine Learning for diagnosis and prognosis of blood-related infections

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Getting started

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Datasets

Name Website Docs Other
MIMIC Physionet -- Article (description)
eICU Physionet Link Article (description)
HiRID Physionet Link ICU Benchmark
AUMCdb Website -- Link

Excellent study on 'Predicting sepsis using deep learning across international sites: a retrospective development and validation study' from Michael Moor et al, published in eClinicalMedicine, 2023 (Article, Supplementary Material, Repository)

MIMIMC

HiRID

eICU

AUMCdb

RICU

The code as it is in the repository does not work. This are just some dingings.

for (x in c("mimic")) {

if (!is_data_avail(x)) { msg("setting up {x}\n") setup_src_data(x) }

dir <- file.path("./") msg("exporting data for {x}\n") export_data(x, dest_dir = dir) }

for (x in c("miiv")) { if (!is_data_avail(x)) { msg("setting up {x}\n") setup_src_data(x) } }

for (x in c("miiv")) { msg("setting up {x}\n") setup_src_data(x) }

for (x in c("miiv")) { if (!is_data_avail(x)) { msg("setting up {x}\n") import_src(x) } }

for (x in c("aumc")) { msg("exporting data for {x}\n") export_data(x) }

dir <- file.path("data-export", paste0("eicu_bernard")) export_data("eicu", dest_dir = dir)

install.packages( c("mimic.demo", "eicu.demo"), repos = "https://eth-mds.github.io/physionet-demo" ) load_concepts("hr", demo, verbose = FALSE) df <- load_concepts("hr", "eicu_demo", verbose = FALSE) write_psv(df, './')

src='eicu' dest_dir <- './' atr <- list( ricu = list( id_vars = id_vars(dat$dat), index_var = index_var(dat$dat), time_unit = units(interval(dat$dat)), time_step = time_step(dat$dat) ), mcsep = list(cohorts = dat$coh) )

dat <- as.data.frame(dat) fil <- file.path(dest_dir, paste(src, packageVersion("ricu"), sep = "_"))

jsonlite::write_json(atr$mcsep$splits, file.path(cfg_path("splits"), paste0(basename(fil), ".json")), pretty = TRUE )

create_parquet(dat, fil, atr, chunk_size = 1e3)

Sys.setenv( RICU_PHYSIONET_USER = "bahp", RICU_PHYSIONET_PASS = "Imperial-5..", RICU_AUMC_TOKEN = "74ca2023-9aab-4f32-a3e6-ebec156b82ab" )

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