Simple Summary This study investigates the latest achievements, challenges, and future
research directions of deep learning techniques for lung cancer and pulmonary nodule …

Lung cancer is a common malignant tumor disease with high clinical disability and death
rates. Currently, lung cancer diagnosis mainly relies on manual pathology section analysis …

Lung cancer is among the most hazardous types of cancer in humans. The correct diagnosis
of pathogenic lung disease is critical for medication. Traditionally, determining the …

Accurate wind power forecasting is of great significance for power system operation. In this
study, a triple-stage multi-step wind power forecasting approach is proposed by applying …

Deep learning has made significant advancements in recent years. The technology is
rapidly evolving and has been used in numerous automated applications with minimal loss …

The spatial heterogeneity is an important indicator of the malignancy of lung nodules in lung
cancer diagnosis. Compared with 2D nodule CT images, the 3D volumes with entire nodule …

Early diagnosis of lung cancer is critical as it can save people's lives. Long-range
dependencies within volumetric medical images are essential attributes for accurate lung …

The feedforward neural network based on randomization has been of great interest in the
scientific community, particularly extreme learning machines, due to its simplicity, training …

Digital twin (DT)-driven intelligent fault diagnosis (IFD) has been a hot topic, which can
support personalized monitoring of critical machinery. A central challenge is that diagnostic …

Selective laser melting is the most commonly used additive manufacturing technique for
fabricating metal components. However, the SLMed part quality still largely suffered from the …