Multimorbidity in middle-aged women and COVID-19: binary data clustering for unsupervised binning of rare multimorbidity features and predictive modeling

Table 1 Cluster Map: Rare features are clustered and mapped to their corresponding cluster (Bins) after feature level clustering

Bin 1	Bin 2	Bin 3		Bin 4	Bin 5			Bin 6		Bin 7		Bin 8	Bin 9	Bin 10	Bin 11
ATC	ATC	ATC	ICD	ATC	ATC	ICD		ATC	ICD	ATC	ICD	ATC	ATC	ATC	ATC
A10BA	A07EC	A03FA	338	G03AA	C01BC	041	550	A07EA	038	B01AA	278	A02BX	A02AD	JO1DD	J01CA
A12AX	B02AA	A05AA	574	G03CA	C01BD	162	560	A10AB	174	B05BB	295	B03BB	A07AA		J01XX
B01AB	C03EA	A12AA	727	G03DB	C01DA	211	562	A10BB	218	C09BX	427	C03CA	B03AA		N06AB
B01AC	C09BA	A12BA	V58	J05AB	C02AC	241	571	C03AA	296	M05BA	455	C08CA	C07AB		R03BA
C09DA	J01AA	B03BA			S01EE	250	585	C03DA	301	N04AA	553	C09AA	H03AA
M01AX	J01DC	C02CA		ICD		298	599	C07AG	454	N05AA	618	C09CA	J02AC
R03AC	J01EE	C03BA		621		354	722	C07BB	473	N05AD	626	C10AA	M01AH
R06AE	M04AA	C07AA				410	780	C10BA	518	N05AH	717	N02AA	N02AX
	N06AA	C09BB				428	786	L01BA	592	S01EC	726	N02CC	N02BE
	P01AB	C10AB				434	813	N01BB	735		812	N03AX
	R03AL	C10AX				437	820	N02AJ	V54		996	N06AX
		D05AX				438	V43	N03AF			998	R03AK
		N02AB				440	V53	P01BA			V64	R06AX
		N02BA				470	V56	R03BB
		N03AE				482	V57	R03DA
		N03AG				486		S01ED

ISSN: 1471-2288