Search Results - "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)

A hybrid GAN-based deep learning framework for thermogram-based breast cancer detection.

Veerlapalli P; Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad, 500075, Telangana, India. preethireddyveerlapalli@gmail.com., Dutta SR; Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad, 500075, Telangana, India.

Journal Article , 2025

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

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

Multivariate quality prediction of thin-walled parts machining using multi-task parallel deep transfer learning.

Wang, Pei^1,2 (AUTHOR) wangpei@xidian.edu.cn, Huang, Pengde^1,2 (AUTHOR), Tao, Haizhen^1,2 (AUTHOR), Liu, Yongkui^1,2 (AUTHOR) yongkuiliu@163.com, Wang, Tao^1,2 (AUTHOR), Qu, Hai^1,2 (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

Deep learning-based image classification and quantification models for tablet sticking.

Kim JY; College of Pharmacy, Daegu Catholic University, Gyeongsan-si, Gyeongbuk 38430, Republic of Korea., Choi DH; College of Pharmacy, Daegu Catholic University, Gyeongsan-si, Gyeongbuk 38430, Republic of Korea. Electronic address: choidh07@cu.ac.kr.

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

Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.

Lin C; State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Department of Liver Tumor Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhouda Road, Baiyun District, Guangzhou, 510515, China.; Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.; Department of Oncology, Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhouda Road, Baiyun District, Guangzhou, Guangdong, 510515, China., Ren Y; University of Electronic Science and Technology of China, Chengdu, China.; Shensi Lab, Shenzhen Institute for Advanced Study, UESTC, Shenzhen, China.; The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China., Huang Y; Department of Pathology, The First Affiliated Hospital of Sun Yat-Sen University, Zhongshan Road II #58, Guangzhou, 510080, People's Republic of China., Li S; Department of Pathology, The First Affiliated Hospital of Sun Yat-Sen University, Zhongshan Road II #58, Guangzhou, 510080, People's Republic of China., Zhang J; Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, China., Kang S; State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Department of Liver Tumor Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhouda Road, Baiyun District, Guangzhou, 510515, China., Li S; Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China., You C; Department of Oncology, Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhouda Road, Baiyun District, Guangzhou, Guangdong, 510515, China. ycx6026@126.com., Cao Q; Department of Pathology, The First Affiliated Hospital of Sun Yat-Sen University, Zhongshan Road II #58, Guangzhou, 510080, People's Republic of China. caoqhua@mail.sysu.edu.cn., Liu F; State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Department of Liver Tumor Center, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhouda Road, Baiyun District, Guangzhou, 510515, China. liufang7250@163.com.; Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China. liufang7250@163.com.

Journal Article , 2025

PhenoDP: leveraging deep learning for phenotype-based case reporting, disease ranking, and symptom recommendation.

Wen B; State Key Laboratory of Genetics and Development of Complex Phenotypes, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China., Shi S; State Key Laboratory of Genetics and Development of Complex Phenotypes, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China., Long Y; School of Medicine, Nankai University, Tianjin, 300071, China., Dang Y; State Key Laboratory of Genetics and Development of Complex Phenotypes, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China., Tian W; State Key Laboratory of Genetics and Development of Complex Phenotypes, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Shanghai, 200438, China. weidong.tian@fudan.edu.cn.; Children's Hospital of Fudan University, Shanghai, 201102, China. weidong.tian@fudan.edu.cn.; Children's Hospital of Shandong University, Jinan, Shandong, 250022, China. weidong.tian@fudan.edu.cn.

Journal Article , 2025

Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography.

Ma Y; Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University, Changsha, Hunan Province, 410008, China., Al-Aroomi MA; Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University, Changsha, Hunan Province, 410008, China., Zheng Y; The College of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan Province, China., Ren W; Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University, Changsha, Hunan Province, 410008, China., Liu P; Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University, Changsha, Hunan Province, 410008, China., Wu Q; High Performance Computing Center, Central South University, Changsha, Hunan Province, China., Liang Y; Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University, Changsha, Hunan Province, 410008, China. liangye@csu.edu.cn., Jiang C; Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University, Changsha, Hunan Province, 410008, China. canhuaj@csu.edu.cn.

Journal Article , 2025

Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome.

Demandt JPA; Department of Cardiology, Catharina Hospital, Eindhoven, Netherlands jesse.demandt@catharinaziekenhuis.nl., Mast TP; Department of Cardiology, Catharina Hospital, Eindhoven, Netherlands., van Beek KAJ; Department of Cardiology, Catharina Hospital, Eindhoven, Netherlands., Koks A; GGD Brabant-Zuidoost, Eindhoven, Noord-Brabant, Netherlands., Bastiaansen MCV; Department of Cardiology, Catharina Hospital, Eindhoven, Netherlands., Tonino PAL; Department of Cardiology, Catharina Hospital, Eindhoven, Netherlands.; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands., van 't Veer M; Department of Cardiology, Catharina Hospital, Eindhoven, Netherlands.; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands., Zimmermann FM; Department of Cardiology, Sint Antonius, Nieuwegein, Utrecht, Netherlands., Vlaar PJ; Department of Cardiology, Catharina Hospital, Eindhoven, Netherlands.

Journal Article , 2025

To Fly, or Not to Fly, That Is the Question: A Deep Learning Model for Peptide Detectability Prediction in Mass Spectrometry.

Abdul-Khalek N; Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark., Picciani M; Computational Mass Spectrometry, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany., Shouman O; Computational Mass Spectrometry, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany., Wimmer R; Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark., Overgaard MT; Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark., Wilhelm M; Computational Mass Spectrometry, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.; Munich Data Science Institute, Technical University of Munich, 85748 Garching, Germany., Gregersen Echers S; Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark.

Journal Article , 2025