81 Result(s)
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Juanjuan Zhao
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Open AccessMitochondrial respiratory chain component NDUFA4: a promising therapeutic target for gastrointestinal cancer
Gastrointestinal cancer, one of the most common cancers, continues to be a major cause of mortality and morbidity globally. Accumulating evidence has shown that alterations in mitochondrial energy metabolism a...
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Open AccessEffective lung nodule detection using deep CNN with dual attention mechanisms
Novel methods are required to enhance lung cancer detection, which has overtaken other cancer-related causes of death as the major cause of cancer-related mortality. Radiologists have long-standing methods for...
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MiR-7 deficiency promotes Th1 polarization of CD4+T cells and enhances the antitumor effect in adoptive cell therapy for lung cancer
Adoptive-cell-therapy (ACT) is important therapeutic approach against cancer. We previously showed that miR-7 deficiency endowed CD4+T cells with hyperactivation status in liver injury. However, whether CD4+T cel...
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Open AccessDCCAFN: deep convolution cascade attention fusion network based on imaging genomics for prediction survival analysis of lung cancer
Recently, lung cancer prediction based on imaging genomics has attracted great attention. However, such studies often have many challenges, such as small sample size, high-dimensional information redundancy, a...
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Open AccessGraph Neural Network for representation learning of lung cancer
The emergence of image-based systems to improve diagnostic pathology precision, involving the intent to label sets or bags of instances, greatly hinges on Multiple Instance Learning for Whole Slide Images(WSIs...
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A progressive phased attention model fused histopathology image features and gene features for lung cancer staging prediction
Identifying the stage of lung cancer accurately from histopathology images and gene is very important for the diagnosis and treatment of lung cancer. Despite the substantial progress achieved by existing metho...
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Open AccessEpithelial plasticity and innate immune activation promote lung tissue remodeling following respiratory viral infection
Epithelial plasticity has been suggested in lungs of mice following genetic depletion of stem cells but is of unknown physiological relevance. Viral infection and chronic lung disease share similar pathologica...
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Residual neural network with mixed loss based on batch training technique for identification of EGFR mutation status in lung cancer
Epidermal growth factor receptor (EGFR) is the key to targeted therapy with tyrosine kinase inhibitors in lung cancer. Traditional identification of EGFR mutation status requires biopsy and sequence testing, w...
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Open AccessBispecific antibodies targeting BCMA, GPRC5D, and FcRH5 for multiple myeloma therapy: latest updates from ASCO 2023 Annual Meeting
Several bispecific antibodies (bsAbs) targeting BCMA, GPRC5D, and FcRH5 are in clinical trials for heavily pretreated multiple myeloma (MM) patients. Teclistamab was approved for relapsed/refractory MM therapy...
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Open AccessCD20 × CD3 bispecific antibodies for lymphoma therapy: latest updates from ASCO 2023 annual meeting
Multiple bispecific antibodies (bsAbs) have been approved for cancer immunotherapy. Several CD20 × CD3 bsAbs have demonstrated significant anti-B-cell non-Hodgkin lymphoma (NHL) activity by engaging T cells to...
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Multi-scale dense selective network based on border modeling for lung nodule segmentation
Accurate quantification of pulmonary nodules helps physicians to accurately diagnose and treat lung cancer. We try to improve the segmentation efficiency of irregular nodules while maintaining the segmentation...
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A segmentation-based sequence residual attention model for KRAS gene mutation status prediction in colorectal cancer
In the computer-aided diagnosis of colorectal cancer, accurate determination of kratom sarcoma (KRAS) gene mutation status is crucial to provide better treatment for patients. In recent years, deep learning me...
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MSTS-Net: malignancy evolution prediction of pulmonary nodules from longitudinal CT images via multi-task spatial-temporal self-attention network
Longitudinal CT images contain the law of lesion growth and evolution over time. Therefore, our purpose is to explore the growth and evolution law of pulmonary lesions in the time dimension to improve the perf...
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Open AccessWeakly supervised label propagation algorithm classifies lung cancer imaging subtypes
Aiming at the problems of long time, high cost, invasive sampling damage, and easy emergence of drug resistance in lung cancer gene detection, a reliable and non-invasive prognostic method is proposed. Under t...
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Open AccessTCR repertoire landscape reveals macrophage-mediated clone deletion in endotoxin tolerance
Endotoxin tolerance (ET) is a protective mechanism in the process of sepsis, septic shock, and their sequelae including uncontrolled inflammation. Accumulating evidence has shown that peripheral T cells contri...
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Attention Matching Network for few-shot learning in the syndrome differentiation of cerebral stroke
Treatment based on Syndrome Differentiation is one of the most important characteristics of Traditional Chinese medicine (TCM). In recent years, Artificial Intelligence (AI) and Deep Learning has played a grea...
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Completion and augmentation-based spatiotemporal deep learning approach for short-term metro origin-destination matrix prediction under limited observable data
Accurate prediction of short-term origin-destination (OD) matrix is crucial for operations in metro systems. Recently, some deep learning-based models have been proposed for OD matrix forecasting in ride-haili...
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DAS-Net: A lung nodule segmentation method based on adaptive dual-branch attention and shadow map**
Quantitative analysis of pulmonary nodules is necessary for the early diagnosis and treatment of lung cancer, improving the possibility of patient survival. Although deep convolutional neural networks (DCNNs) ...
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Semantic consistency generative adversarial network for cross-modality domain adaptation in ultrasound thyroid nodule classification
Deep convolutional networks have been widely used for various medical image processing tasks. However, the performance of existing learning-based networks is still limited due to the lack of large training dat...
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MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data
Medical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, development, or extinction). We try to explore the evolution process of l...
