ML-MEDIC: A Preliminary Study of an Interactive Visual Analysis Tool Facilitating Clinical Applications of Machine Learning for Precision Medicine.
cloud computing
data science
data-driven medicine
interactive visual analysis
machine learning
Journal
Applied sciences (Basel, Switzerland)
ISSN: 2076-3417
Titre abrégé: Appl Sci (Basel)
Pays: Switzerland
ID NLM: 101633495
Informations de publication
Date de publication:
May 2020
May 2020
Historique:
entrez:
5
3
2021
pubmed:
6
3
2021
medline:
6
3
2021
Statut:
ppublish
Résumé
Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC's efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also conducted to obtain an impression of the usability and potential limitations.
Identifiants
pubmed: 33664984
doi: 10.3390/app10093309
pmc: PMC7928533
mid: NIHMS1616468
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : NLM NIH HHS
ID : T15 LM009451
Pays : United States
Déclaration de conflit d'intérêts
Conflicts of Interest: The authors declare no conflicts of interest.
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