Sökresultat - "Deep Learning"

Heterogeneous knowledge graph-driven subassembly identification with ensemble deep learning in Industry 4.0.

Zhang, Chao^1,2 (AUTHOR), Jing, Yanzhen² (AUTHOR), Zhou, Guanghui^1,2 (AUTHOR) ghzhou@mail.xjtu.edu.cn, Yan, Hairui² (AUTHOR), Chang, Fengtian³ (AUTHOR)

Advancing label-free cell classification with connectome-inspired explainable models and a novel LIVECell-CLS dataset.

Fiore P; NeuRoNe Lab, University of Salerno, Via Giovanni Paolo II, 132, Fisciano, 84084, SA, Italy. Electronic address: pifiore@unisa.it., Terlizzi A; NeuRoNe Lab, University of Salerno, Via Giovanni Paolo II, 132, Fisciano, 84084, SA, Italy. Electronic address: aterlizzi@unisa.it., Bardozzo F; NeuRoNe Lab, University of Salerno, Via Giovanni Paolo II, 132, Fisciano, 84084, SA, Italy. Electronic address: fbardozzo@unisa.it., Liò P; Computer Laboratory, University of Cambridge, William Gates Building 15 J J Thomson Avenue, Cambridge, CB3 0FD, United Kingdom. Electronic address: pl219@cam.ac.uk., Tagliaferri R; NeuRoNe Lab, University of Salerno, Via Giovanni Paolo II, 132, Fisciano, 84084, SA, Italy. Electronic address: robtag@unisa.it.

Journal Article , 2025

ORAKLE: Optimal Risk prediction for mAke30 in patients with sepsis associated AKI using deep LEarning.

Oh W; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Division of Data-Driven and Digital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Veshtaj M; Touro College of Osteopathic Medicine, New York, NY, USA.; Department of Cardiovascular Surgery, Mount Sinai Morningside, New York, NY, USA., Sawant A; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Division of Data-Driven and Digital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Division of Hospital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Agrawal P; Improbable AI Lab, Massachusetts Institute of Technology, Cambridge, MA, USA., Gomez H; Department of Critical Care Medicine, Center for Critical Care Nephrology, University of Pittsburgh, Pittsburgh, PA, USA., Suarez-Farinas M; Department of Population Health Science and Policy, Center for Biostatistics, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Oropello J; Institute for Critical Care Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Kohli-Seth R; Institute for Critical Care Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Kashani K; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, USA.; Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA., Kellum JA; Department of Critical Care Medicine, Center for Critical Care Nephrology, University of Pittsburgh, Pittsburgh, PA, USA., Nadkarni G; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Division of Data-Driven and Digital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA., Sakhuja A; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ankit.sakhuja@mssm.edu.; Division of Data-Driven and Digital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ankit.sakhuja@mssm.edu.; Institute for Critical Care Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA. ankit.sakhuja@mssm.edu.

Journal Article , 2025

Multi-Energy Evaluation of Image Quality in Spectral CT Pulmonary Angiography Using Different Strength Deep Learning Spectral Reconstructions.

Hosseini-Siyanaki M; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.)., Sagdic HS; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.)., Raviprasad AG; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.)., Munjerin SE; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.)., Prodigios JC; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.)., Anthony EY; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.)., Hochhegger B; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.)., Forghani R; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.); Division of Medical Physics, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Neurology, Division of Movement Disorders, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Otolaryngology - Head and Neck Surgery, McGill University, Montreal, Quebec, Canada (R.F.); Department of Radiology, AdventHealth Medical Group, Maitland, FL (R.F.). Electronic address: reza.forghani.md@adventhealth.com.

Journal Article , 2025

Deep Learning Reconstruction for Enhanced Resolution and Image Quality in Breath-Hold MRCP: A Preliminary Study.

Shiraishi K; Departments of Diagnostic Radiology., Nakaura T; Departments of Diagnostic Radiology., Yoshida N; Departments of Diagnostic Radiology., Matsuo K; Department of Central Radiology, Kumamoto University Hospital, Kumamoto, Japan., Kobayashi N; Departments of Diagnostic Radiology., Hokamura M; Departments of Diagnostic Radiology., Uetani H; Departments of Diagnostic Radiology., Nagayama Y; Departments of Diagnostic Radiology., Kidoh M; Departments of Diagnostic Radiology., Morita K; Department of Central Radiology, Kumamoto University Hospital, Kumamoto, Japan., Yamashita Y; Canon Medical Systems Corporation, Kanagawa, Japan., Tanaka Y; Gastroenterology and Hepatology., Baba H; Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan., Hirai T; Departments of Diagnostic Radiology.

Journal Article , 2025

Extraction of fetal heartbeat locations in abdominal phonocardiograms using deep attention transformer.

Almadani MM; Khalifa University, Department of Biomedical Engineering and Biotechnology, Abu Dhabi, 127788, United Arab Emirates. Electronic address: 100060577@ku.ac.ae., Alkhodari M; Khalifa University, Department of Biomedical Engineering and Biotechnology, Abu Dhabi, 127788, United Arab Emirates; University of Oxford, Cardiovascular Clinical Research Facility, Radcliffe Department of Medicine, Oxford, OX1 4BH, UK., Ghosh SK; Khalifa University, Department of Biomedical Engineering and Biotechnology, Abu Dhabi, 127788, United Arab Emirates., Hadjileontiadis L; Khalifa University, Department of Biomedical Engineering and Biotechnology, Abu Dhabi, 127788, United Arab Emirates; Aristotle University of Thessaloniki, Department of Electrical and Computer Engineering, Thessaloniki, 54124, Greece., Khandoker A; Khalifa University, Department of Biomedical Engineering and Biotechnology, Abu Dhabi, 127788, United Arab Emirates.

Journal Article , 2025

Vision transformer and deep learning based weighted ensemble model for automated spine fracture type identification with GAN generated CT images.

D N S; Department of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India., Pai RM; Department of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India. radhika.pai@manipal.edu., Bhat SN; Department of Orthopaedics, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India., Pai MMM; Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.

Journal Article , 2025

A new bundling model to promote the worst selling products with deep learning approaches.

Weng, Cheng-Hsiung¹ (AUTHOR) bmahck@ccu.edu.tw, Huang, Cheng-Kui² (AUTHOR)

Rapid detection of the viability of naturally aged maize seeds using multimodal data fusion and explainable deep learning techniques.

Li H; College of Agronomy and Biotechnology, China Agricultural University/ The Innovation Center (Beijing) of Crop Seeds Whole-Process Technology Research of Ministry of Agriculture and Rural Affairs/Beijing Key Laboratory of Crop Genetic Improvement, Beijing 100193, China., Mao Y; College of Agronomy and Biotechnology, China Agricultural University/ The Innovation Center (Beijing) of Crop Seeds Whole-Process Technology Research of Ministry of Agriculture and Rural Affairs/Beijing Key Laboratory of Crop Genetic Improvement, Beijing 100193, China., Xu Y; College of Agronomy and Biotechnology, China Agricultural University/ The Innovation Center (Beijing) of Crop Seeds Whole-Process Technology Research of Ministry of Agriculture and Rural Affairs/Beijing Key Laboratory of Crop Genetic Improvement, Beijing 100193, China., Tu K; Jiangsu Key Laboratory of Crop Genetics and Physiology, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding (Agricultural College of Yangzhou University), Research Institute of Smart Agriculture (Agricultural College of Yangzhou University), Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225009, China., Zhang H; College of Agronomy and Biotechnology, China Agricultural University/ The Innovation Center (Beijing) of Crop Seeds Whole-Process Technology Research of Ministry of Agriculture and Rural Affairs/Beijing Key Laboratory of Crop Genetic Improvement, Beijing 100193, China., Gu R; College of Agronomy and Biotechnology, China Agricultural University/ The Innovation Center (Beijing) of Crop Seeds Whole-Process Technology Research of Ministry of Agriculture and Rural Affairs/Beijing Key Laboratory of Crop Genetic Improvement, Beijing 100193, China., Sun Q; College of Agronomy and Biotechnology, China Agricultural University/ The Innovation Center (Beijing) of Crop Seeds Whole-Process Technology Research of Ministry of Agriculture and Rural Affairs/Beijing Key Laboratory of Crop Genetic Improvement, Beijing 100193, China.. Electronic address: sunqun@cau.edu.cn.

Journal Article; Evaluation Study , 2025

A general deep learning model for predicting and classifying pea protein content via visible and near-infrared spectroscopy.

Xiao T; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Xie C; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Yang L; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China. Electronic address: yangli@cau.edu.cn., He X; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Wang L; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Zhang D; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Cui T; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Zhang K; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Li H; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China., Dong J; College of Engineering, China Agricultural University, Beijing 100083, China; The Soil-Machine-Plant key Laboratory of the Ministry of Agriculture of China, Beijing 100083, China.

Journal Article; Evaluation Study , 2025

Lightweight deep learning model for embedded systems efficiently predicts oil and protein content in rapeseed.

Guo M; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China., Ma H; Agricultural Products Processing Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang 524001, PR China., Lv X; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China., Wang D; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China., Fu L; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China., He P; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China., Mei D; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China., Chen H; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China., Wei F; Key Laboratory of Oilseeds Processing of Ministry of Agriculture, Hubei Key Laboratory of Lipid Chemistry and Nutrition, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan, Hubei 430062, PR China; Hubei Hongshan Laboratory, Wuhan, Hubei 430070, PR China. Electronic address: willasa@163.com.

Journal Article; Evaluation Study , 2025

A multimodal deep learning model for detecting endoscopic images of near-infrared fluorescence capsules.

Wang J; School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China., Zhou C; School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China., Wang W; School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China., Zhang H; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address: hanxiao.zhang@sjtu.edu.cn., Zhang A; Department of Food Science & Technology, School of Agriculture & Biology, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address: zhangamin@sjtu.edu.cn., Cui D; School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Medical and Engineering Cross Research Institute, School of Medicine, Henan University, Kaifeng, 475004, China. Electronic address: dxcui@sjtu.edu.cn.

Journal Article , 2025

Discovery of naturally inspired antimicrobial peptides using deep learning.

Yang CL; College of Pharmaceutical Science & Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang key laboratory of green, low-carbon, and efficient development of Marine Fishery Resources, Zhejiang University of Technology, Hangzhou 310014, China., Wang PP; Department of Endocrinology and Metabolism, The Fifth Affiliated Hospital, Sun Yat-Sen University, Zhuhai, Guangdong 519000, China., Zhou ZY; College of Pharmaceutical Science & Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang key laboratory of green, low-carbon, and efficient development of Marine Fishery Resources, Zhejiang University of Technology, Hangzhou 310014, China., Wu XW; College of Pharmaceutical Science & Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang key laboratory of green, low-carbon, and efficient development of Marine Fishery Resources, Zhejiang University of Technology, Hangzhou 310014, China., Hua Y; College of Pharmaceutical Science & Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang key laboratory of green, low-carbon, and efficient development of Marine Fishery Resources, Zhejiang University of Technology, Hangzhou 310014, China., Chen JW; College of Pharmaceutical Science & Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang key laboratory of green, low-carbon, and efficient development of Marine Fishery Resources, Zhejiang University of Technology, Hangzhou 310014, China., Wang H; College of Pharmaceutical Science & Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang key laboratory of green, low-carbon, and efficient development of Marine Fishery Resources, Zhejiang University of Technology, Hangzhou 310014, China; Binjiang Institute of Artificial Intelligence, ZJUT, Hangzhou 310051, China.. Electronic address: hongw@zjut.edu.cn., Wei B; College of Pharmaceutical Science & Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals, Zhejiang key laboratory of green, low-carbon, and efficient development of Marine Fishery Resources, Zhejiang University of Technology, Hangzhou 310014, China; Binjiang Institute of Artificial Intelligence, ZJUT, Hangzhou 310051, China.. Electronic address: binwei@zjut.edu.cn.

Journal Article , 2025

Automated Measurements of Spinal Parameters for Scoliosis Using Deep Learning.

Meng X; Department of Radiology, Tianjin University Tianjin Hospital, Hexi District, Tianjin, China., Zhu S; Department of Radiology, Tianjin University Tianjin Hospital, Hexi District, Tianjin, China., Yang Q; Department of Radiology, Tianjin University Tianjin Hospital, Hexi District, Tianjin, China., Zhu F; Department of Radiology, Tianjin University Tianjin Hospital, Hexi District, Tianjin, China., Wang Z; Department of Radiology, Tianjin University Tianjin Hospital, Hexi District, Tianjin, China., Liu X; Beijing United Imaging Research Institute of Intelligent Imaging, Haidian District, Beijing, China., Dong P; United Imaging Intelligence (Beijing) Co. Ltd, Haidian District, Beijing, China., Wang S; Beijing United Imaging Research Institute of Intelligent Imaging, Haidian District, Beijing, China., Fan L; United Imaging Intelligence (Beijing) Co. Ltd, Haidian District, Beijing, China.

Journal Article , 2025

A review of multimodal fusion-based deep learning for Alzheimer's disease.

Zhang R; School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China; Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of P. R. China, Hangzhou, Zhejiang 310018, China., Sheng J; School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China; Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of P. R. China, Hangzhou, Zhejiang 310018, China. Electronic address: j.sheng@ieee.org., Zhang Q; Beijing Hospital, Beijing 100730, China; National Center of Gerontology, Beijing 100730, China; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China. Electronic address: zhangqiao2941@bjhmoh.cn., Wang J; School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China; Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of P. R. China, Hangzhou, Zhejiang 310018, China., Wang B; School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China; Key Laboratory of Intelligent Image Analysis for Sensory and Cognitive Health, Ministry of Industry and Information Technology of P. R. China, Hangzhou, Zhejiang 310018, China.

Journal Article; Review , 2025

Enhanced EEG-based Alzheimer's disease detection using synchrosqueezing transform and deep transfer learning.

Jain S; Department of Computer Science and Engineering, Indian Institute of Technology (IIT), BHU, Varanasi Uttar Pradesh, India, 221011. Electronic address: Shraddhajain.rs.cse22@itbhu.ac.in., Srivastava R; Department of Computer Science and Engineering, Indian Institute of Technology (IIT), BHU, Varanasi Uttar Pradesh, India, 221011. Electronic address: rajeev.cse@itbhu.ac.in.

Journal Article , 2025

Web server-based deep learning-driven predictive models for respiratory toxicity of environmental chemicals: Mechanistic insights and interpretability.

Li N; Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China., Chen Z; Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China., Zhang W; Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China., Li Y; Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China., Huang X; Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China., Li X; Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China. Electronic address: lixiao1688@163.com.

Journal Article , 2025

Efficient detection of foodborne pathogens via SERS and deep learning: An ADMIN-optimized NAS-Unet approach.

Wang Z; College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China., Liang P; College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China. Electronic address: plianghust@gmail.com., Zhai J; School of Electrical and Information Engineering, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300072, China., Wu B; RD Department, Zhejiang Uniview Technologies Co., Ltd, Hangzhou 310051, China., Chen X; College of Optical and Electronic Technology, China Jiliang University, Hangzhou 310018, China., Ding F; College of Energy Environment and Safety Engineering, China Jiliang University, No. 258 Xueyuan Street, Qiantang District, Hangzhou, Zhejiang Province 310018, China; College of Metrology and Measurement Engineering, China Jiliang University, No. 258 Xueyuan Street, Qiantang District, Hangzhou, Zhejiang Province 310018, China., Chen Q; College of Energy Environment and Safety Engineering, China Jiliang University, No. 258 Xueyuan Street, Qiantang District, Hangzhou, Zhejiang Province 310018, China; College of Metrology and Measurement Engineering, China Jiliang University, No. 258 Xueyuan Street, Qiantang District, Hangzhou, Zhejiang Province 310018, China., Sun B; School of Electrical and Information Engineering, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300072, China. Electronic address: sunbiao@tju.edu.cn.

Journal Article , 2025

Ensemble learning of deep CNN models and two stage level prediction of Cobb angle on surface topography in adolescents with idiopathic scoliosis.

Hassan M; Department of Mechanical Engineering, University of Alberta, 10th Floor, Donadeo Innovation Centre for Engineering, Edmonton, T6G 1H9, AB, Canada; Mechanical Design & Production Department, Faculty of Engineering, Cairo University, Cairo University Rd, Oula, Giza District, Cairo, 12613, Egypt. Electronic address: mkhassan@ualberta.ca., Gonzalez Ruiz JM; Department of Mechanical Engineering, University of Alberta, 10th Floor, Donadeo Innovation Centre for Engineering, Edmonton, T6G 1H9, AB, Canada., Mohamed N; Department of Mechanical Engineering, University of Alberta, 10th Floor, Donadeo Innovation Centre for Engineering, Edmonton, T6G 1H9, AB, Canada., Burke TN; Allied Health Institute, Federal University of Mato Grosso do Sul, Cidade Universitária, Av. Costa e Silva, Campo Grande, 79070-900, MS, Brazil., Mei Q; Department of Civil and Environmental Engineering, University of Alberta, 7th Floor, Donadeo Innovation Centre for Engineering, Edmonton, T6G 1H9, AB, Canada., Westover L; Department of Mechanical Engineering, University of Alberta, 10th Floor, Donadeo Innovation Centre for Engineering, Edmonton, T6G 1H9, AB, Canada; Department of Biomedical Engineering, University of Alberta, 13th Floor, Donadeo Innovation Centre for Engineering, Edmonton, T6G 1H9, AB, Canada.

Journal Article , 2025

An Optimized Framework of QSM Mask Generation Using Deep Learning: QSMmask-Net.

Lee G; Department of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea., Jung W; AIRS Medical, Seoul, Republic of Korea., Sakaie KE; Department of Diagnostic Radiology, Diagnostics Institute, The Cleveland Clinic, Cleveland, Ohio, USA., Oh SH; Department of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea.; Department of Diagnostic Radiology, Diagnostics Institute, The Cleveland Clinic, Cleveland, Ohio, USA.

Journal Article , 2025