Results 151 to 160 of about 9,883,756 (332)

Transformer‐Based Multitask Framework Integrating Habitat and Deep Learning for Predicting Early Disease Control and Survival in Immunotherapy‐Treated Hepatocellular Carcinoma

Advanced Science, EarlyView.
This study developed ECOS‐Net, a transformer‐based multitask framework integrating CT‐derived habitat and 2.5D deep learning features to simultaneously predict early disease control and overall survival in hepatocellular carcinoma patients treated with immune checkpoint inhibitors.
Xiaona Fu, Yusheng Guo, Bingxin Gong, Jie Lou, Ning Wang, Xuejun Chen, Hongtao Hu, Rundong Wang, Xiaofang Guo, Shanmei Li, Yangyang Xie, Shichao Long, Mengsi Li, Shubo Pan, Wen Shen, Zhaogang Zhang, Zifang Song, Pengchen Liang, Xiaoyun Liang, Peng Sun, Guilin Zhang, Shanshan Jiang, Jinxiang Zhang, Lian Yang   +23 more
wiley   +1 more source

Drug Repurposing for Treating NCOR‐Related Intellectual Disability

Advanced Science, EarlyView.
An autism‐associated NCOR1 heterozygous mutation upregulates NRGs and activates NRG backward signaling in hypothalamic GABAergic neurons in mouse models, leading to Gabra2 downregulation and cognitive deficits, which can be therapeutically targeted by repurposing FDA‐approved drugs.
Yan Kong, Wenjun Zhou, Yuxiang Sun, Zihan Huang, Zhiyue Liu, Udhaya Kumar. S, Chenyan Li, Yi Lu, Chengchuang Song, Veronica C. Ciliberto, Makenna Mack, Lana E. Kim, Zhaoyong Hu, Fang Luo, Aihua Cao, Zheng Sun   +15 more
wiley   +1 more source

Mitochondrial Protection and Neural Repair via ROS‐Responsive Biomimetic Nanoparticles in Intracerebral Hemorrhage

Advanced Science, EarlyView.
A ROS‐responsive biomimetic nanoparticle platform co‐delivers DIDS and Mdivi‐1 to protect mitochondria and promote neural repair after intracerebral hemorrhage. By targeting LPAR1/VDAC1‐related mitochondrial dysfunction, the nanotherapy reduces oxidative injury, neuronal apoptosis, and blood‐brain barrier disruption, improving neurological recovery and
Ling Gao, Li Peng, Xiaobin Zheng, Cong Tan, Chuang Wang, Qijiang Xiong, Weiming Chen, Zhao Yang   +7 more
wiley   +1 more source

DL-AMC: Deep Learning for Automatic Modulation Classification

Automatic Modulation Classification (AMC) is a signal processing technique widely used at the physical layer of wireless systems to enhance spectrum utilization efficiency. In this work, we propose a fast and accurate AMC system, termed DL-AMC, which leverages deep learning techniques.
Rehman, Faheem Ur, Abbas, Qamar, Shehzad, M. Karam   +2 more
openaire   +2 more sources

Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities

AIMS Public Health
In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications.
Anichur Rahman, Tanoy Debnath, Dipanjali Kundu, Md. Saikat Islam Khan, A. Aishi, Sadia Sazzad, Mohammad Sayduzzaman, Shahab S. Band   +7 more
semanticscholar   +1 more source

Transformer‐Based PET/CT Fusion Enables Preoperative Prediction and Prognostic Stratification of Spread Through Air Spaces in Lung Adenocarcinoma

Advanced Science, EarlyView.
An eight‐stream 2.5D Transformer integrates complementary PET metabolic and CT morphologic information to estimate spread‐through‐air‐spaces risk before surgery in lung adenocarcinoma. The model generalizes across independent centers, while its continuous risk score independently stratifies progression‐free survival, supporting further prospective ...
Xin‐Yu Zhu, Meng Meng, Zhen‐Zhen Wang, Deng‐Lu Lu, Ya‐Min Wei, Xu‐Chang Mi, Xing‐Yu Mu, Wei Fu   +7 more
wiley   +1 more source

Revolutionizing crop disease detection with computational deep learning: a comprehensive review

Environmental Monitoring & Assessment
Digital image processing has witnessed a significant transformation, owing to the adoption of deep learning (DL) algorithms, which have proven to be vastly superior to conventional methods for crop detection.
H. Ngugi, A. Ezugwu, A. A. Akinyelu, L. Abualigah   +3 more
semanticscholar   +1 more source

An Integrated Artificial Intelligence Framework for Nanomedicine Engineering

Advanced Science, EarlyView.
This review outlines a closed‐loop AI ecosystem for nanomedicine engineering. By synergizing multimodal data harmonization, objective‐driven AI architectures, and automated high‐throughput validation, this “Design‐Make‐Test‐Analyze” (DMTA) workflow transforms traditional heuristic formulation into a predictive, self‐optimizing paradigm, accelerating ...
Meichen Dong, Qin Luo, Xinyi Ding, Chaoqi Lu, Ru Zhang, Qingqing Tan, Zhiqing Pang, Defang Ouyang, Dongsheng Li, Jiaxuan Xia, Jianxin Wang   +10 more
wiley   +1 more source

Deep learning for accelerated and robust MRI reconstruction

Magnetic Resonance Materials in Physics, Biology and Medicine
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic resonance imaging (MRI), a critical tool in diagnostic radiology.
Reinhard Heckel, Mathews Jacob, A. Chaudhari, Or Perlman, Efrat Shimron   +4 more
semanticscholar   +1 more source

Massively Multiplexed Photonic Chip With Cross‐Channel Fusion For Harmonized Biosensing

Advanced Science, EarlyView.
We introduce a transformative sensing platform integrating photonic multiplexing with over 10 000 sensors and a deep‐learning framework that combines domain adaptation and cross‐channel fusion for harmonized operation across heterogeneous chips. The platform achieves 99.3% identification accuracy and relative prediction errors of 10−4$^{-4}$ for ...
Ivan Saetchnikov, Elina Tcherniavskaia, Andreas Ostendorf, Anton Saetchnikov   +3 more
wiley   +1 more source