A5026412038- Lung Cancer Diagnosis and Treatment
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Topic Modeling
- Biomedical Text Mining and Ontologies
- Conducting polymers and applications
- Natural Language Processing Techniques
- Glass properties and applications
- Recycling and utilization of industrial and municipal waste in materials production
- Polydiacetylene-based materials and applications
- Mineralogy and Gemology Studies
- Translation Studies and Practices
- Diverse multidisciplinary academic research
- Multilevel Inverters and Converters
- Society, Economy, and Ethics Research
- Electric Motor Design and Analysis
- Antimicrobial agents and applications
- Mycobacterium research and diagnosis
- Silicone and Siloxane Chemistry
- Advanced Nanomaterials in Catalysis
- Cancer-related molecular mechanisms research
- Synthesis and properties of polymers
- Water-Energy-Food Nexus Studies
- Water resources management and optimization
- MicroRNA in disease regulation
Donghua University
2023
Zhejiang University
2021-2022
Harbin Institute of Technology
2022
Ministry of Education of the People's Republic of China
2021
East China University of Science and Technology
2019
Tang Hospital
2019
Guangdong University of Technology
2019
Beijing Foreign Studies University
2018
Lung cancer is the leading cause of deaths worldwide. Clinical staging lung plays a crucial role in making treatment decisions and evaluating prognosis. However, clinical practice, approximately one-half stages patients are inconsistent with their pathological stages. As one most important diagnostic modalities for staging, chest computed tomography (CT) provides wealth information about but free-text nature CT reports obstructs computerization.
Lymph node metastasis (LNM) is critical for treatment decision making of patients with resectable non-small cell lung cancer, but it difficult to precisely diagnose preoperatively. Electronic medical records (EMRs) contain a large volume valuable information about LNM, some key recorded in free text, which hinders its secondary use.This study aims develop LNM prediction models based on EMRs using natural language processing (NLP) and machine learning algorithms.We developed multiturn...
A retranslation of a given text can be produced with an awareness pre-existing translation in the same target language. The results are textual similarities and/or differences between and its predecessor. These attest to relationship two (re)translations. This paper refers this as 'the intertextual (re)translations' these 'intertextuality retranslation' (IR). By comparing three English versions Chinese short story, 'Kong Yiji', intends shed light via practical analysis (re)translations...
Computed tomography (CT) reports record a large volume of valuable information about patients' conditions and the interpretations radiology images from radiologists, which can be used for clinical decision-making further academic study. However, free-text nature is critical barrier to use this data more effectively. In study, we investigate novel deep learning method extract entities Chinese CT lung cancer screening TNM staging.The proposed approach presents new named entity recognition...
Axial flux motor design is normally depended on a designer's experience to adjust parameters, which vague and complex, for example, torque density ripple are two key factors of restrain its development, since dominates motor's volume weight, while determines stability. Therefore, general optimizations methodology required in process. To realize this purpose, paper proposes multi-objective optimization practical design. In detail, based Support Vector Machine-Chaotic Cultural Differential...
Recently, silicone rubber (VMQ) was extensively used in household articles and medical devices. To develop a kind of safe long‐term antimicrobial VMQ great significance. In this work, vinyl‐contained polyhexamethylene guanidine hydrochloride (VPHMG) synthesized as additive for VMQ. With the increasing VPHMG addition, mechanical properties VMQ‐VPHMG were significantly improved. particular, rates against Escherichia coli Staphylococcus aureus higher than 99.99% 4 wt% addition. Moreover,...
Abstract Background Lung cancer is the leading cause of death worldwide. Prognostic prediction plays a vital role in decision-making process for postoperative non-small cell lung (NSCLC) patients. However, high imbalance ratio prognostic data limits development effective models. Methods In this study, we present novel approach, namely ensemble learning with active sampling (ELAS), to tackle imbalanced problem NSCLC prediction. ELAS first applies an mechanism query most informative samples...
Abstract Climate change will exacerbate water scarcity, as warmer temperatures increase evaporation from soil and surfaces, raising crop requirements, consumers’ demand for energy at higher temperatures, with a concomitant in cooling water. Therefore, scarcity has evolved into global issue, most notably the Colorado Basin. As climate changes, future of River becomes even more tragic. The river’s levels are dropping year after year, while needs surrounding urban development increasing, what...
<sec> <title>BACKGROUND</title> Lung cancer is the leading cause of deaths worldwide. Clinical staging lung plays a crucial role in making treatment decisions and evaluating prognosis. However, clinical practice, approximately one-half stages patients are inconsistent with their pathological stages. As one most important diagnostic modalities for staging, chest computed tomography (CT) provides wealth information about but free-text nature CT reports obstructs computerization. </sec>...
<sec> <title>BACKGROUND</title> Lymph node metastasis (LNM) is critical for treatment decision making of patients with resectable non–small cell lung cancer, but it difficult to precisely diagnose preoperatively. Electronic medical records (EMRs) contain a large volume valuable information about LNM, some key recorded in free text, which hinders its secondary use. </sec> <title>OBJECTIVE</title> This study aims develop LNM prediction models based on EMRs using natural language processing...