arXiv Open Access 2023

TemporAI: Facilitating Machine Learning Innovation in Time Domain Tasks for Medicine

Evgeny S. Saveliev Mihaela van der Schaar
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Abstrak

TemporAI is an open source Python software library for machine learning (ML) tasks involving data with a time component, focused on medicine and healthcare use cases. It supports data in time series, static, and eventmodalities and provides an interface for prediction, causal inference, and time-to-event analysis, as well as common preprocessing utilities and model interpretability methods. The library aims to facilitate innovation in the medical ML space by offering a standardized temporal setting toolkit for model development, prototyping and benchmarking, bridging the gaps in the ML research, healthcare professional, medical/pharmacological industry, and data science communities. TemporAI is available on GitHub (https://github.com/vanderschaarlab/temporai) and we welcome community engagement through use, feedback, and code contributions.

Topik & Kata Kunci

Penulis (2)

E

Evgeny S. Saveliev

M

Mihaela van der Schaar

Format Sitasi

Saveliev, E.S., Schaar, M.v.d. (2023). TemporAI: Facilitating Machine Learning Innovation in Time Domain Tasks for Medicine. https://arxiv.org/abs/2301.12260

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓