Machine learning for electrocatalyst and photocatalyst design and discovery
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …
reducing the impact of global warming, and providing solutions to environmental pollution …
A guide to machine learning for biologists
The expanding scale and inherent complexity of biological data have encouraged a growing
use of machine learning in biology to build informative and predictive models of the …
use of machine learning in biology to build informative and predictive models of the …
Deep learning in cancer diagnosis, prognosis and treatment selection
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning
technique called artificial neural networks to extract patterns and make predictions from …
technique called artificial neural networks to extract patterns and make predictions from …
Classification based on decision tree algorithm for machine learning
B Charbuty, A Abdulazeez - Journal of Applied Science and Technology …, 2021 - jastt.org
Decision tree classifiers are regarded to be a standout of the most well-known methods to
data classification representation of classifiers. Different researchers from various fields and …
data classification representation of classifiers. Different researchers from various fields and …
A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics
We present the application of a class of deep learning, known as Physics Informed Neural
Networks (PINN), to inversion and surrogate modeling in solid mechanics. We explain how …
Networks (PINN), to inversion and surrogate modeling in solid mechanics. We explain how …
Artificial intelligence aids in development of nanomedicines for cancer management
P Tan, X Chen, H Zhang, Q Wei, K Luo - Seminars in cancer biology, 2023 - Elsevier
Over the last decade, the nanomedicine has experienced unprecedented development in
diagnosis and management of diseases. A number of nanomedicines have been approved …
diagnosis and management of diseases. A number of nanomedicines have been approved …
[HTML][HTML] Architected cellular materials: A review on their mechanical properties towards fatigue-tolerant design and fabrication
M Benedetti, A Du Plessis, RO Ritchie… - Materials Science and …, 2021 - Elsevier
Additive manufacturing of industrially-relevant high-performance parts and products is today
a reality, especially for metal additive manufacturing technologies. The design complexity …
a reality, especially for metal additive manufacturing technologies. The design complexity …
Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing
The outbreak of COVID-19 Coronavirus, namely SARS-CoV-2, has created a calamitous
situation throughout the world. The cumulative incidence of COVID-19 is rapidly increasing …
situation throughout the world. The cumulative incidence of COVID-19 is rapidly increasing …
Machine learning algorithm validation with a limited sample size
Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other
technology-based data collection methods have led to a torrent of high dimensional …
technology-based data collection methods have led to a torrent of high dimensional …
Wilds: A benchmark of in-the-wild distribution shifts
Distribution shifts—where the training distribution differs from the test distribution—can
substantially degrade the accuracy of machine learning (ML) systems deployed in the wild …
substantially degrade the accuracy of machine learning (ML) systems deployed in the wild …