Machine learning for electrocatalyst and photocatalyst design and discovery

H Mai, TC Le, D Chen, DA Winkler… - Chemical …, 2022 - ACS Publications
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …

The impacts of ocean acidification on marine ecosystems and reliant human communities

SC Doney, DS Busch, SR Cooley… - Annual Review of …, 2020 - annualreviews.org
Racism. Sexism. Heterosexism. Gender binarism. Together, they comprise intimately
harmful, distinct, and entangled societal systems of self-serving domination and privilege …

Machine learning algorithm validation with a limited sample size

A Vabalas, E Gowen, E Poliakoff, AJ Casson - PloS one, 2019 - journals.plos.org
Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other
technology-based data collection methods have led to a torrent of high dimensional …

Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling

YP Zhang, XY Zhang, YT Cheng, B Li, XZ Teng… - Military Medical …, 2023 - Springer
Modern medicine is reliant on various medical imaging technologies for non-invasively
observing patients' anatomy. However, the interpretation of medical images can be highly …

POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability

F Li, Y Zhou, Y Zhang, J Yin, Y Qiu… - Briefings in …, 2022 - academic.oup.com
Mass spectrometry-based proteomic technique has become indispensable in current
exploration of complex and dynamic biological processes. Instrument development has …

Machine Learning-Guided Development of Trialkylphosphine Ni(I) Dimers and Applications in Site-Selective Catalysis

TM Karl, S Bouayad-Gervais, JA Hueffel… - Journal of the …, 2023 - ACS Publications
Owing to the unknown correlation of a metal's ligand and its resulting preferred speciation in
terms of oxidation state, geometry, and nuclearity, a rational design of multinuclear catalysts …

A machine learning-based framework to identify type 2 diabetes through electronic health records

T Zheng, W **e, L Xu, X He, Y Zhang, M You… - International journal of …, 2017 - Elsevier
Objective To discover diverse genotype-phenotype associations affiliated with Type 2
Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide …

[PDF][PDF] Machine learning in epidemiology and health outcomes research

TL Wiemken, RR Kelley - Annu Rev Public Health, 2020 - datascienceassn.org
Abstract Machine learning approaches to modeling of epidemiologic data are becoming
increasingly more prevalent in the literature. These methods have the potential to improve …

A Photochemical Strategy for the Conversion of Nitroarenes into Rigidified Pyrrolidine Analogues

E Matador, MJ Tilby, I Saridakis, M Pedrón… - Journal of the …, 2023 - ACS Publications
Bicyclic amines are important motifs for the preparation of bioactive materials. These species
have well-defined exit vectors that enable accurate disposition of substituents toward …

REVISE: A tool for measuring and mitigating bias in visual datasets

A Wang, A Liu, R Zhang, A Kleiman, L Kim… - International Journal of …, 2022 - Springer
Abstract Machine learning models are known to perpetuate and even amplify the biases
present in the data. However, these data biases frequently do not become apparent until …