[HTML][HTML] Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review

E Afsaneh, A Sharifdini, H Ghazzaghi… - Diabetology & Metabolic …, 2022 - Springer
Diabetes as a metabolic illness can be characterized by increased amounts of blood
glucose. This abnormal increase can lead to critical detriment to the other organs such as …

[HTML][HTML] Applications of artificial intelligence algorithms in the energy sector

H Szczepaniuk, EK Szczepaniuk - Energies, 2022 - mdpi.com
The digital transformation of the energy sector toward the Smart Grid paradigm, intelligent
energy management, and distributed energy integration poses new requirements for …

Short-term rockburst prediction in underground project: Insights from an explainable and interpretable ensemble learning model

Y Qiu, J Zhou - Acta Geotechnica, 2023 - Springer
Rockburst is a frequent challenge during tunnel and other underground construction and is
an extreme rock damage phenomenon. Therefore, it is very crucial to accurately estimate the …

Machine learning–assisted molecular design and efficiency prediction for high-performance organic photovoltaic materials

W Sun, Y Zheng, K Yang, Q Zhang, AA Shah, Z Wu… - Science …, 2019 - science.org
In the process of finding high-performance materials for organic photovoltaics (OPVs), it is
meaningful if one can establish the relationship between chemical structures and …

State of health estimation for lithium-ion battery based on energy features

D Gong, Y Gao, Y Kou, Y Wang - Energy, 2022 - Elsevier
There is a recognized need to forecast lithium-ion batteries' state of health (SOH) to
guarantee their safety and reliability. However, the selected health indicators highly …

An effective dual self-attention residual network for seizure prediction

X Yang, J Zhao, Q Sun, J Lu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
As one of the most challenging data analysis tasks in chronic brain diseases, epileptic
seizure prediction has attracted extensive attention from many researchers. Seizure …

Soft computing-based EEG classification by optimal feature selection and neural networks

MH Bhatti, J Khan, MUG Khan, R Iqbal… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Brain computer interface translates electroencephalogram (EEG) signals into control
commands so that paralyzed people can control assistive devices. This human thought …

[HTML][HTML] Applications of electronic nose, electronic eye and electronic tongue in quality, safety and shelf life of meat and meat products: a review

PES Munekata, S Finardi, CK de Souza, C Meinert… - Sensors, 2023 - mdpi.com
The quality and shelf life of meat and meat products are key factors that are usually
evaluated by complex and laborious protocols and intricate sensory methods. Devices with …

CIUSuite 2: next-generation software for the analysis of gas-phase protein unfolding data

DA Polasky, SM Dixit, SM Fantin… - Analytical chemistry, 2019 - ACS Publications
Ion mobility–mass spectrometry (IM–MS) has become an important addition to the structural
biology toolbox, but separating closely related protein conformations remain challenging …

From bit to bedside: a practical framework for artificial intelligence product development in healthcare

D Higgins, VI Madai - Advanced intelligent systems, 2020 - Wiley Online Library
Artificial intelligence (AI) in healthcare holds great potential to expand access to high‐quality
medical care, while reducing systemic costs. Despite hitting headlines regularly and many …