Machine learning to predict safety signals using molecular similarity and disproportionate reporting rates

Research output: Contribution to journal › Conference Abstract/Poster in journal › Academic

Original language	English
Pages (from-to)	456-456
Number of pages	1
Journal	Pharmacoepidemiology and Drug Safety
Volume	31
Issue number	SI
Publication status	Published - 1 Sept 2022

Cite this

@article{bb11fa93e1c44a32a229b400b7247901,

title = "Machine learning to predict safety signals using molecular similarity and disproportionate reporting rates",

author = "L.A. Quirant and A. Rudolph and R. Cavill and E.L. Meldau",

year = "2022",

month = sep,

day = "1",

language = "English",

volume = "31",

pages = "456--456",

journal = "Pharmacoepidemiology and Drug Safety",

issn = "1053-8569",

publisher = "John Wiley \& Sons Inc.",

number = "SI",

}

TY - JOUR

T1 - Machine learning to predict safety signals using molecular similarity and disproportionate reporting rates

AU - Quirant, L.A.

AU - Rudolph, A.

AU - Cavill, R.

AU - Meldau, E.L.

PY - 2022/9/1

Y1 - 2022/9/1

M3 - Conference Abstract/Poster in journal

SN - 1053-8569

VL - 31

SP - 456

EP - 456

JO - Pharmacoepidemiology and Drug Safety

JF - Pharmacoepidemiology and Drug Safety

IS - SI

ER -