Machine learning approach to study drug effects and identification of signals from symptomatic and asymptomatic mutation carries using iPSC-derived cardiomyocytes

Martti Juhola; Henry Joutsijoki; Kirsi Penttinen; Katriina Aalto-Setälä

doi:10.1016/j.imu.2025.101631

Machine learning approach to study drug effects and identification of signals from symptomatic and asymptomatic mutation carries using iPSC-derived cardiomyocytes

Martti Juhola, Henry Joutsijoki, Kirsi Penttinen, Katriina Aalto-Setälä

Research output: Contribution to journal › Article › Scientific › peer-review

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Original language	English
Article number	101631
Number of pages	13
Journal	Informatics in Medicine Unlocked
Volume	54
DOIs	https://doi.org/10.1016/j.imu.2025.101631
Publication status	Published - 9 Mar 2025
Publication type	A1 Journal article-refereed

Keywords

Cardiac diseases
Drugs
Human induced pluripotent stem cell-derived cardiomyocytes
Machine learning methods
Classification

Publication forum classification

Publication forum level 1

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.imu.2025.101631Licence: CC BY

Machine learning approach to study drug effects and identification of signals from symptomatic and asymptomatic mutation carries using iPSC-derived cardiomyocytesFinal published version, 1.21 MBLicence: CC BY

https://urn.fi/URN:NBN:fi:tuni-202503112693Licence: CC BY

Cite this

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title = "Machine learning approach to study drug effects and identification of signals from symptomatic and asymptomatic mutation carries using iPSC-derived cardiomyocytes",

keywords = "Cardiac diseases, Drugs, Human induced pluripotent stem cell-derived cardiomyocytes, Machine learning methods, Classification",

author = "Martti Juhola and Henry Joutsijoki and Kirsi Penttinen and Katriina Aalto-Set{\"a}l{\"a}",

year = "2025",

month = mar,

day = "9",

doi = "10.1016/j.imu.2025.101631",

language = "English",

volume = "54",

}

Machine learning approach to study drug effects and identification of signals from symptomatic and asymptomatic mutation carries using iPSC-derived cardiomyocytes. / Juhola, Martti ; Joutsijoki, Henry; Penttinen, Kirsi et al.
In: Informatics in Medicine Unlocked, Vol. 54, 101631, 09.03.2025.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - Machine learning approach to study drug effects and identification of signals from symptomatic and asymptomatic mutation carries using iPSC-derived cardiomyocytes

AU - Juhola, Martti

AU - Joutsijoki, Henry

AU - Penttinen, Kirsi

AU - Aalto-Setälä, Katriina

PY - 2025/3/9

Y1 - 2025/3/9

KW - Cardiac diseases

KW - Drugs

KW - Human induced pluripotent stem cell-derived cardiomyocytes

KW - Machine learning methods

KW - Classification

U2 - 10.1016/j.imu.2025.101631

DO - 10.1016/j.imu.2025.101631

M3 - Article

SN - 2352-9148

VL - 54

JO - Informatics in Medicine Unlocked

JF - Informatics in Medicine Unlocked

M1 - 101631

ER -