00887nas a2200325   4500000000100000000000100001000000100002008004100003653001100044653003100055653003400086653002500120653002000145653004800165653002400213653001500237653001500252653001600267100001200283700001400295700001800309700001600327700001700343700001200360245014500372250001500517300000800532490000700540020001400547       2023                            d10aHumans10a*Electronic Health Records10aUnsupervised Machine Learning10aEngland/epidemiology10aHospitalization10a*Acute Kidney Injury/epidemiology/diagnosis10aAcute kidney injury10aClustering10aPhenotypes10aSeasonality1 aH. Bolt1 aA. Suffel1 aJ. Matthewman1 aF. Sandmann1 aL. Tomlinson1 aR. Eggo00aSeasonality of acute kidney injury phenotypes in England: an unsupervised machine learning classification study of electronic health records  a2023/08/10  a2340 v24  a1471-2369