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Causal machine learning for predicting treatment outcomes
Nature MedicineCausal machine learning (ML) offers flexible, data-driven methods for predicting treatment outcomes including efficacy and toxicity, thereby supporting the assessment and safety of drugs.
S. Feuerriegel +9 more
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Flink-ML: machine learning in Apache Flink
Brazilian Journal of TechnologyThe emergence of Big Data has spurred the development of various frameworks designed for efficient data storage and processing. Key frameworks include Hadoop, Spark, Flink, Storm, Pig, and Zookeeper. Among these, Apache Flink stands out as a prominent open-source platform known for its powerful stream and batch processing capabilities.
Messaoud Mezati, Ines Aouria
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Medical and Biological Engineering and Computing, 2020
N. Mahmood +5 more
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N. Mahmood +5 more
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Nature Machine Intelligence
One of the most promising applications of machine learning in computational physics is to accelerate the solution of partial differential equations (PDEs).
Nick McGreivy, Ammar Hakim
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One of the most promising applications of machine learning in computational physics is to accelerate the solution of partial differential equations (PDEs).
Nick McGreivy, Ammar Hakim
semanticscholar +1 more source
Machine learning for microbiologists
Nature Reviews Microbiology, 2023Francesco Asnicar +2 more
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A guide to machine learning for biologists
Nature Reviews Molecular Cell Biology, 2021Joe G Greener +2 more
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Machine learning methods to model multicellular complexity and tissue specificity
Nature Reviews Materials, 2021Aaron K Wong, Olga G Troyanskaya
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Machine Learning (ML) and Toxicity Studies
2022Shyamasree Ghosh, Rathi Dasgupta
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Machine learning sheds light on microbial dark proteins
Nature Reviews Microbiology, 2023Aaron T Hammack, Crysten E Blaby-Haas
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