The three prediction tasks for AI and clinical and therapeutic matches
ML task
Medical task
Therapeutic strategy
AF detection
AF diagnosis
Anticoagulant
Identifying patients who will develop AF
AF prevention
Lifestyle changes
Predicting the onset of AF
AF avoidance
PITP
AI: artificial intelligence; ML: machine learning; AF: atrial fibrillation; PITP: pill in the pocket
Declarations
Author contributions
JMG: Conceptualization, Investigation, Writing—original draft, Writing—review & editing. CG and FM: Software, Validation, Funding acquisition. HB and SC: Validation, Writing—review & editing, Supervision. All authors read and approved the submitted version.
Conflicts of interest
The authors declare that they have no conflicts of interest.
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent to publication
Not applicable.
Availability of data and materials
Not applicable.
Funding
This work was supported in part by the French Community of Belgium [FRIA funding: FC 038733]; this project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement [No 101034383]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Open Exploration maintains a neutral stance on jurisdictional claims in published institutional affiliations and maps. All opinions expressed in this article are the personal views of the author(s) and do not represent the stance of the editorial team or the publisher.
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