A review of radiomics and genomics applications in cancers: the way towards precision medicine

S Li, B Zhou - Radiation Oncology, 2022 - Springer
The application of radiogenomics in oncology has great prospects in precision medicine.
Radiogenomics combines large volumes of radiomic features from medical digital images …

Scaling multiobjective evolution to large data with minions: A Bayes-informed multitask approach

Z Chen, A Gupta, L Zhou, YS Ong - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In an era of pervasive digitalization, the growing volume and variety of data streams poses a
new challenge to the efficient running of data-driven optimization algorithms. Targeting …

An innovative ensemble model based on deep learning for predicting COVID-19 infection

X Su, Y Sun, H Liu, Q Lang, Y Zhang, J Zhang… - Scientific Reports, 2023 - nature.com
Nowadays, global public health crises are occurring more frequently, and accurate
prediction of these diseases can reduce the burden on the healthcare system. Taking …

Research on fault diagnosis system for belt conveyor based on internet of things and the LightGBM model

M Wang, K Shen, C Tai, Q Zhang, Z Yang, C Guo - Plos one, 2023 - journals.plos.org
As an equipment failure that often occurs in coal production and transportation, belt
conveyor failure usually requires many human and material resources to be identified and …

Runoff probability prediction model based on natural Gradient boosting with tree-structured parzen estimator optimization

K Shen, H Qin, J Zhou, G Liu - Water, 2022 - mdpi.com
Accurate and reliable runoff prediction is critical for solving problems related to water
resource planning and management. Deterministic runoff prediction methods cannot meet …

Flip-chip solder bumps defect detection using a self-search lightweight framework

Y Sun, L Su, J Gu, X Zhao, K Li, M Pecht - Advanced Engineering …, 2024 - Elsevier
The flip-chip technology is widely used in aerospace and defense electronic systems
because of its high information processing, rapid response and autonomous control. As flip …

Multitask Learning for Quantitative Structure–Activity Relationships: A Tutorial

C Valsecchi, F Grisoni, V Consonni, D Ballabio… - Machine Learning and …, 2023 - Springer
Multitask learning allows to model multiple tasks simultaneously through information
sharing. In the context of quantitative structure–activity relationships and computational …

Fatigue fracture mechanisms and life prediction of welded S310-S321 joints at high temperature

Z Shen, Z Huang, J Wang, H Qian, Q Zhou… - Engineering Fracture …, 2024 - Elsevier
Austenitic stainless steel is prevalent in the manufacturing of aircraft structural components
and chemical pipelines, which are frequently subjected to high temperatures. To investigate …

A novel multitask learning algorithm for tasks with distinct chemical space: zebrafish toxicity prediction as an example

RH Lin, P Lin, CC Wang, CW Tung - Journal of Cheminformatics, 2024 - Springer
Data scarcity is one of the most critical issues impeding the development of prediction
models for chemical effects. Multitask learning algorithms leveraging knowledge from …

Enhanced prediction of end-point carbon content in electric arc furnaces using Bayesian optimised fully connected neural networks with early stopping

H Zhu, H Lu, Z Jiang, H Li, C Yang, Z Ni… - Ironmaking & …, 2024 - journals.sagepub.com
This study developed a Bayesian optimisation-enhanced fully connected neural network
(BO-EFCNN) model with an early stopping mechanism to predict the end-point carbon …