A5069424444- Water Quality Monitoring and Analysis
- Spectroscopy and Chemometric Analyses
- Spectroscopy Techniques in Biomedical and Chemical Research
- Pregnancy and preeclampsia studies
- COVID-19 diagnosis using AI
- Maternal and fetal healthcare
- Autonomous Vehicle Technology and Safety
- Foot and Ankle Surgery
- Radiomics and Machine Learning in Medical Imaging
- Cerebral Palsy and Movement Disorders
- Diabetic Foot Ulcer Assessment and Management
- Topic Modeling
- Phonocardiography and Auscultation Techniques
- Lung Cancer Diagnosis and Treatment
- Remote Sensing and Land Use
- Data Quality and Management
- Acupuncture Treatment Research Studies
- Geotechnical Engineering and Soil Mechanics
- Augmented Reality Applications
- Environmental Education and Sustainability
- Thermal Radiation and Cooling Technologies
- Text and Document Classification Technologies
- Sleep and Work-Related Fatigue
- Uterine Myomas and Treatments
- Gestational Trophoblastic Disease Studies
East China Normal University
2022-2025
Yanshan University
2021-2024
Central South University
2020-2024
Xi'an Jiaotong University
2024
CHN Energy (China)
2024
Sichuan University
2022-2023
The Fourth People's Hospital
2022
Lanzhou Jiaotong University
2022
Duke Medical Center
2020
Prediction of isocitrate dehydrogenase (IDH) mutation status and epilepsy occurrence are important to glioma patients. Although machine learning models have been constructed for both issues, the correlation between them has not explored. Our study aimed exploit this improve performance IDH identification diagnosis in patients with II-IV. 399 were retrospectively enrolled divided into a training (n = 279) an independent test 120) cohort. Multi-center dataset 228) from The Cancer Imaging...
Abstract Microalgae have been widely commercially cultivated, and their cell concentration is crucial for determining key cultivation parameters such as light intensity, temperature, nutrient concentration. Absorption fluorescence spectra are effective methods detecting microalgal However, absorption weak prone to interference at low concentrations, while affected by the inner filter effect high concentrations. To overcome these limitations, this study proposes a prediction method based on...
Pneumoconiosis staging has been a very challenging task, both for certified radiologists and computer-aided detection algorithms. Although deep learning shown proven advantages in the of pneumoconiosis, it remains pneumoconiosis due to stage ambiguity noisy samples caused by misdiagnosis when they are used training models. In this article, we propose fully paradigm that comprises segmentation procedure procedure. The extracts lung fields chest radiographs through an Asymmetric...
Fatigue-related traffic accidents have a higher mortality rate and cause more significant damage to the environment. To ensure driving safety, real-time driver fatigue detection method based on convolutional neural network (CNN) is proposed in this paper. The cascaded by two CNN-based stages, including detecting phase classifying phase. Location Detection Network designed extract facial features localize driver's eyes mouth regions. Then State Recognition training recognize status....
Personality characteristics represent the behavioral of a class people. Social networking sites have multitude users, and text messages generated by them convey person’s feelings, thoughts, emotions at particular time. These social texts indeed record long-term psychological activities which can be used for research on personality recognition. However, most existing deep learning models multi-label classification consider long-distance semantics or sequential semantics, but problems such as...
Traditional multi-label text classification methods, especially deep learning, have achieved remarkable results, but most of these methods use the word2vec technique to represent continuous information, which fails fully capture semantic information text. To solve this problem, we built a hierarchical Transformer-CNN model and applied it in classification. Taking into account characteristics natural language, is constructed different levels at word sentence using multi-headed self-attention...
Text classification is the most common application of Natural Language Processing(NLP), and Transformer models have dominated field in recent years. Currently, pre-training modeling text through deep learning methods a way classification. This paper firstly proposes an improved XLNet model based on problems long-term dependence insufficient contextual semantic expression previous pre-trained language models, uses to represent as low-dimensional word vectors obtain sequences. Secondly,...
Abstract We aimed to establish a computerized diagnostic model predict placenta accrete spectrum (PAS) disorders based on T2-weighted MR imaging. recruited pregnant women with clinically suspected PAS between January 2015 and December 2018 in our institution. All preoperative imaging (T2WI) images were manually outlined the picture archive communication system terminal server. A nnU-Net network for automatic segmentation corresponding radiomics features extracted from segmented region...
Spectral non-contact detection technology has shown great potential in predicting the growth trend of microorganisms ocean. By applying spectral for online real-time characteristics, monitoring concentration ocean and achieving their prediction, this can effectively respond to imminent outbreak marine ecological pollution. In study, a system based on ultraviolet spectroscopy (UV) combined with PPSA model(1DCNN-PLSR Parallel 1DCNN-SVR Adaptation, PPSA) was provided microbial prediction...
Spectral non-contact detection technology has shown great potential in predicting the growth trend of microorganisms ocean. By applying spectral for online real-time characteristics, monitoring concentration ocean and achieving their prediction, this can effectively respond to imminent outbreak marine ecological pollution. In study, a system based on ultraviolet spectroscopy (UV) combined with PPSA model(1DCNN-PLSR Parallel 1DCNN-SVR Adaptation, PPSA) was provided microbial prediction...
Placenta accreta spectrum (PAS) is a pathologic condition of placentation associated with significant maternal morbidity and mortality. We enrolled 540 patients from two institutions to build an automatic pipeline for early diagnosis PAS based on T2W images. An nnU-Net model was trained segmentation the placenta, then image stripe created, in which utero-placental borderline (UPB) straightened centered. The UPB fed into DenseNet-based network together placental position diagnosis. achieved...
Abstract With the increasing emphasis on refinement of reactor thermal hydraulic calculations, research multi-scale coupled models nuclear has also developed. This article utilizes self-developed lead bismuth system analysis program SACLER, combined with mature commercial CFD software FLUENT, to develop a suitable for 1D/3D calculations fast reactors. In order ensure accuracy developed coupling program, calculation function was first verified through simple circular tube case. The matches...
Author Name Disambiguation (AND) is a crucial task in the knowledge engineering of bibliography. In academic search systems, author name ambiguity common phenomenon caused by different authors with same and leads to that can not be used reliably identify all scholar authors. recent researches, one papers' attributes are often learn its representation as feature. However, most existing methods ignore extract deep features potential relationship among papers. To address problem, we propose...