Results 221 to 230 of about 154,707 (286)

Preoperative VEGFR‐TKI Plus ICI Therapy Facilitates 3D‐Guided Cytoreductive Nephron‐Sparing Surgical Feasibility and Immune Remodeling in Advanced Renal Cell Carcinoma

Med Research, EarlyView.
Preoperative VEGFR‐TKI plus ICI therapy in advanced ccRCC normalizes tumor vasculature, enhances CD8⁺ T/B cell infiltration, and promotes TLS maturation, leading to profound tumor microenvironment remodeling. These immunologic changes improve the feasibility of 3D reconstruction‐guided robotic cytoreductive nephron‐sparing surgery, resulting in reduced
Wenhao Xu, Aihetaimujiang Anwaier, Qintao Ge, Siqi Zhou, Xi Tian, Shuxuan Zhu, Guohai Shi, Yu Zhu, Dingwei Ye, Mierxiati Abudurexiti, Hailiang Zhang   +10 more
wiley   +1 more source

Attention-based multi-agent reinforcement learning for traffic flow stability in mountainous tunnel entrances. [PDF]

Sci Rep
Duan M.
europepmc   +1 more source

Spatio-temporal transformer and graph convolutional networks based traffic flow prediction. [PDF]

Sci Rep
Zhang J, Yang Y, Wu X, Li S.
europepmc   +1 more source

An efficient intelligent transportation system for traffic flow prediction using meta-temporal hyperbolic quantum graph neural networks. [PDF]

Sci Rep
Rajagopal M, Sivasakthivel R, Anitha G, Arunachalam KP, Loganathan K, Abbas M, Kalathil S, Rao KS.   +7 more
europepmc   +1 more source

Empirical study of daily link traffic volume forecasting based on a deep neural network. [PDF]

PLoS One
Eom JK, Lee KS, Min JH, Kwak HC.
europepmc   +1 more source

Hybrid signal decomposition and deep learning framework for vehicle-vehicle crash forecasting. [PDF]

Sci Rep
Zhou J, Khattak A, Mao X, Chen F, Xing L, Zhang Z.   +5 more
europepmc   +1 more source

Pretraining-improved Spatiotemporal graph network for the generalization performance enhancement of traffic forecasting. [PDF]

Sci Rep
Zhang X, Li C, Ji L, Kang Y, Pan M, Liu Z, Qi Q.   +6 more
europepmc   +1 more source

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Short-Term Traffic Flow Prediction: Using LSTM

2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3), 2020
Traffic data is being exploded in past few years and that is because of the increasing number of vehicles. People get struck in the traffic for hours so, accurate flow of traffic is really important for both the traveler and intelligent transportation system. Existing models somehow fails to provide accurate information of flow and that is because they
Pregya Poonia, V. K. Jain
openaire   +1 more source

Short-term traffic flow prediction: From the perspective of traffic flow decomposition

Neurocomputing, 2020
Abstract Some researchers treat traffic flow as an entirety while predicting short-term traffic flow. Through analyzing real-world traffic flow, we have found that urban traffic shows a stable changing process along with random disturbs. An alternative way is to decompose traffic flow into two components: periodicity and volatility.
Li Chen, Linjiang Zheng, Jie Yang, Dong Xia, Weining Liu   +4 more
openaire   +1 more source

Short-term traffic flow prediction in bike-sharing networks

Journal of Intelligent Transportation Systems, 2021
For station-based bike-sharing systems, the balance between user demand and bike allocation is critical for the operation.
Bo Wang, Hai L. Vu, Inhi Kim, Chen Cai
openaire   +1 more source