Publications by authors named "Linghao Chen"

An emergency water pollution incident poses a significant risk to the proper functioning of wastewater treatment plants, particularly in domestic-industrial integrated facilities. Source tracing is recognized as an effective method to mitigate ongoing impacts. Machine learning-assisted traceability is emerging as a more efficient and faster method compared to traditional methods.

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Mammography screening is instrumental in the early detection and diagnosis of breast cancer by identifying masses in mammograms. With the rapid development of deep learning, numerous deep learning-based object detection algorithms have been explored for mass detection studies. However, these methods often yield a high false positive rate per image (FPPI) while achieving a high true positive rate (TPR).

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Article Synopsis
  • - The study explores the use of drones (UAVs) combined with artificial intelligence (AI) to improve rapid triage processes after mass-casualty incidents (MCIs), aiming to enhance emergency response efficiency.
  • - Researchers developed an intelligent triage system utilizing AI algorithms, OpenPose and YOLO, tested in a simulated MCI scene with volunteer actors, incorporating real-time data transmission via 5G.
  • - Results indicated that the new system effectively recognized seven key postures for triage, suggesting it could serve as an innovative alternative method in emergency rescue scenarios.
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DNA methylation plays an important role in Parkinson's disease (PD) pathogenesis. DNA methyltransferase 1 (DNMT1) is critical for maintaining DNA methylation in mammals. The link between polymorphisms and PD remains elusive.

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Introduction: Parkinson's disease (PD) is highly heterogeneous in manifestations and pathogenesis. Serotonergic neurotransmitter system dysfunction is frequently implicated in PD tremor. Serotonin (5-HT) content in platelets is highly correlated with that in cerebrospinal fluid.

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In this paper, we propose a novel system named Disp R-CNN for 3D object detection from stereo images. Many recent works solve this problem by first recovering point clouds with disparity estimation and then apply a 3D detector. The disparity map is computed for the entire image, which is costly and fails to leverage category-specific prior.

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