Presenting a prediction model for HELLP syndrome through data mining

Table 2 The dataset features and their descriptions

Type	Row	Feature	Type	Role
Base-line	1	Mother-age	Quantitative	Input
	2	Gestational-age	Quantitative	Input
	3	Gravidity	Quantitative	Input
	4	Abortion	Quantitative	Input
	5	Mother-BMI	Quantitative	Input
	6	Twin	Qualitative (No = 0, Yes = 1)	Input
Clinical	7	Systolic-Blood-pressure	Quantitative	Input
	8	Systolic-Blood-pressure	Quantitative	Input
	9	Epigaster pain	Qualitative (No = 0, Yes = 1)	Input
	10	Headache	Qualitative (No = 0, Yes = 1)	Input
	11	Nausea	Qualitative (No = 0, Yes = 1)	Input
Biomarker	12	Bili-T	Quantitative	Input
	13	Bili-D	Quantitative	Input
	14	Creatinine	Quantitative	Input
	15	Lactate Dehydrogenase (LDH)	Quantitative	Input
	16	AST	Quantitative	Input
	17	ALT	Quantitative	Input
	18	FBS	Quantitative	Input
	19	Platelet	Quantitative	Input
	20	Hemoglobin	Quantitative	Input
Outcome	21	Diagnosis	Qualitative (Preeclampsia = 0, HELLP Syndrome = 1)	Target

ISSN: 1472-6947