Artificial intelligence in molecular medicine
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Facebook Twitter Instagram YouTube LinkedIn Prepare to become a physician, build your …
Facebook Twitter Instagram YouTube LinkedIn Prepare to become a physician, build your …
Machine learning for precision medicine
SJ MacEachern, ND Forkert - Genome, 2021 - cdnsciencepub.com
Precision medicine is an emerging approach to clinical research and patient care that
focuses on understanding and treating disease by integrating multi-modal or multi-omics …
focuses on understanding and treating disease by integrating multi-modal or multi-omics …
Crop breeding for a changing climate: Integrating phenomics and genomics with bioinformatics
Key message Safeguarding crop yields in a changing climate requires bioinformatics
advances in harnessing data from vast phenomics and genomics datasets to translate …
advances in harnessing data from vast phenomics and genomics datasets to translate …
Exploitation of surrogate variables in random forests for unbiased analysis of mutual impact and importance of features
LF Voges, LC Jarren, S Seifert - Bioinformatics, 2023 - academic.oup.com
Motivation Random forest is a popular machine learning approach for the analysis of high-
dimensional data because it is flexible and provides variable importance measures for the …
dimensional data because it is flexible and provides variable importance measures for the …
[HTML][HTML] Genome-wide association studies of soybean yield-related hyperspectral reflectance bands using machine learning-mediated data integration methods
M Yoosefzadeh-Najafabadi, S Torabi… - Frontiers in plant …, 2021 - frontiersin.org
In conjunction with big data analysis methods, plant omics technologies have provided
scientists with cost-effective and promising tools for discovering genetic architectures of …
scientists with cost-effective and promising tools for discovering genetic architectures of …
Harnessing the potential of machine learning and artificial intelligence for dementia research
Progress in dementia research has been limited, with substantial gaps in our knowledge of
targets for prevention, mechanisms for disease progression, and disease-modifying …
targets for prevention, mechanisms for disease progression, and disease-modifying …
Interpretable machine learning for genomics
DS Watson - Human genetics, 2022 - Springer
High-throughput technologies such as next-generation sequencing allow biologists to
observe cell function with unprecedented resolution, but the resulting datasets are too large …
observe cell function with unprecedented resolution, but the resulting datasets are too large …
Applications of artificial intelligence in clinical laboratory genomics
S Aradhya, FM Facio, H Metz, T Manders… - American Journal of …, 2023 - Wiley Online Library
The transition from analog to digital technologies in clinical laboratory genomics is ushering
in an era of “big data” in ways that will exceed human capacity to rapidly and reproducibly …
in an era of “big data” in ways that will exceed human capacity to rapidly and reproducibly …
The musical abilities, pleiotropy, language, and environment (MAPLE) framework for understanding musicality-language links across the lifespan
Using individual differences approaches, a growing body of literature finds positive
associations between musicality and language-related abilities, complementing prior …
associations between musicality and language-related abilities, complementing prior …
Machine learning and big data provide crucial insight for future biomaterials discovery and research
J Kerner, A Dogan, H von Recum - Acta Biomaterialia, 2021 - Elsevier
Abstract Machine learning have been widely adopted in a variety of fields including
engineering, science, and medicine revolutionizing how data is collected, used, and stored …
engineering, science, and medicine revolutionizing how data is collected, used, and stored …