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Wyszukujesz frazę ""Deep Learning"" wg kryterium: Temat


Starter badań:

Tytuł:
Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques.
Autorzy:
Civit-Masot J; Architecture and Computer Technology department (ATC), Robotics and Technology of Computers Lab (RTC), E.T.S. Ingeniería Informática, Avda. Reina Mercedes s/n, Universidad de Sevilla, Seville, 41012, Spain.
Bañuls-Beaterio A; Architecture and Computer Technology department (ATC), Robotics and Technology of Computers Lab (RTC), E.T.S. Ingeniería Informática, Avda. Reina Mercedes s/n, Universidad de Sevilla, Seville, 41012, Spain.
Domínguez-Morales M; Architecture and Computer Technology department (ATC), Robotics and Technology of Computers Lab (RTC), E.T.S. Ingeniería Informática, Avda. Reina Mercedes s/n, Universidad de Sevilla, Seville, 41012, Spain; Computer Engineering Research Institute (I3US), E.T.S. Ingeniería Informática, Avda. Reina Mercedes s/n, Universidad de Sevilla, Seville, 41012, Spain. Electronic address: .
Rivas-Pérez M; Architecture and Computer Technology department (ATC), Robotics and Technology of Computers Lab (RTC), E.T.S. Ingeniería Informática, Avda. Reina Mercedes s/n, Universidad de Sevilla, Seville, 41012, Spain.
Muñoz-Saavedra L; Architecture and Computer Technology department (ATC), Robotics and Technology of Computers Lab (RTC), E.T.S. Ingeniería Informática, Avda. Reina Mercedes s/n, Universidad de Sevilla, Seville, 41012, Spain.
Rodríguez Corral JM; Computer Science department, School of Engineering, Avda. Universidad de Cádiz 10, Universidad de Cádiz, Puerto Real (Cádiz), 11519, Spain.
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Źródło:
Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2022 Nov; Vol. 226, pp. 107108. Date of Electronic Publication: 2022 Sep 07.
Typ publikacji:
Journal Article
MeSH Terms:
Carcinoma, Non-Small-Cell Lung*/diagnostic imaging
Deep Learning*
Lung Neoplasms*/diagnostic imaging
Adenocarcinoma*
Humans ; Artificial Intelligence
Czasopismo naukowe
Tytuł:
Symbolic Deep Networks: A Psychologically Inspired Lightweight and Efficient Approach to Deep Learning.
Autorzy:
Veksler VD; DCS Corp, Alexandria, VA.; Human Systems Integration Division (HSID), U.S. Army DEVCOM Data & Analysis Center (DAC).
Hoffman BE; Human Systems Integration Division (HSID), U.S. Army DEVCOM Data & Analysis Center (DAC).
Buchler N; Human Systems Integration Division (HSID), U.S. Army DEVCOM Data & Analysis Center (DAC).
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Źródło:
Topics in cognitive science [Top Cogn Sci] 2022 Oct; Vol. 14 (4), pp. 702-717. Date of Electronic Publication: 2021 Oct 05.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Artificial Intelligence ; Neural Networks, Computer ; Machine Learning ; Cognitive Science
Czasopismo naukowe
Tytuł:
Application of deep learning methods: From molecular modelling to patient classification.
Autorzy:
Fu X; Biomolecular Modelling Laboratory, The Francis Crick Institute, 1 Midland Rd, London, NW1 1AT, UK. Electronic address: .
Bates PA; Biomolecular Modelling Laboratory, The Francis Crick Institute, 1 Midland Rd, London, NW1 1AT, UK. Electronic address: .
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Źródło:
Experimental cell research [Exp Cell Res] 2022 Sep 15; Vol. 418 (2), pp. 113278. Date of Electronic Publication: 2022 Jul 08.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Deep Learning*
Neural Networks, Computer*
Computer Simulation ; Humans ; Machine Learning
Czasopismo naukowe
Tytuł:
An Edge-Based Selection Method for Improving Regions-of-Interest Localizations Obtained Using Multiple Deep Learning Object-Detection Models in Breast Ultrasound Images.
Autorzy:
Daoud MI; Department of Computer Engineering, German Jordanian University, Amman-Madaba Street, Amman 11180, Jordan.
Al-Ali A; Department of Computer Engineering, German Jordanian University, Amman-Madaba Street, Amman 11180, Jordan.
Alazrai R; Department of Computer Engineering, German Jordanian University, Amman-Madaba Street, Amman 11180, Jordan.
Al-Najar MS; Department of Diagnostic Radiology, The University of Jordan Hospital, Queen Rania Al-Abdullah Street, Amman 11942, Jordan.
Alsaify BA; Department of Network Engineering and Security, Jordan University of Science & Technology, Irbid 22110, Jordan.
Ali MZ; Department of Computer Information Systems, Jordan University of Science & Technology, Irbid 22110, Jordan.
Alouneh S; Cybersecurity Program, College of Engineering, Al Ain University, 28th Street, Abu Dhabi, United Arab Emirates.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Sep 06; Vol. 22 (18). Date of Electronic Publication: 2022 Sep 06.
Typ publikacji:
Journal Article
MeSH Terms:
Breast Neoplasms*/diagnostic imaging
Breast Neoplasms*/pathology
Deep Learning*
Diagnosis, Computer-Assisted ; Female ; Humans ; Ultrasonography, Mammary/methods
Czasopismo naukowe
Tytuł:
Ensemble deep learning for the prediction of proficiency at a virtual simulator for robot-assisted surgery.
Autorzy:
Moglia A; EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Edificio 102, via Paradisa 2, 56124, Pisa, Italy. .
Morelli L; EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Edificio 102, via Paradisa 2, 56124, Pisa, Italy.; General Surgery Unit, Cisanello Teaching Hospital of Pisa, 56124, Pisa, Italy.; Multidisciplinary Center of Robotic Surgery, University Hospital of Pisa, 56124, Pisa, Italy.
D'Ischia R; General Surgery Unit, Cisanello Teaching Hospital of Pisa, 56124, Pisa, Italy.
Fatucchi LM; General Surgery Unit, Cisanello Teaching Hospital of Pisa, 56124, Pisa, Italy.
Pucci V; General Surgery Unit, Cisanello Teaching Hospital of Pisa, 56124, Pisa, Italy.
Berchiolli R; Vascular Surgery Unit, Cisanello Teaching Hospital of Pisa, 56124, Pisa, Italy.
Ferrari M; EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Edificio 102, via Paradisa 2, 56124, Pisa, Italy.; Vascular Surgery Unit, Cisanello Teaching Hospital of Pisa, 56124, Pisa, Italy.
Cuschieri A; Scuola Superiore Sant'Anna of Pisa, 56214, Pisa, Italy.; Institute for Medical Science and Technology, University of Dundee, Dundee, DD2 1FD, UK.
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Źródło:
Surgical endoscopy [Surg Endosc] 2022 Sep; Vol. 36 (9), pp. 6473-6479. Date of Electronic Publication: 2022 Jan 12.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Robotic Surgical Procedures*/education
Artificial Intelligence ; Clinical Competence ; Computer Simulation ; Humans
Czasopismo naukowe
Tytuł:
A geometry-informed deep learning framework for ultra-sparse 3D tomographic image reconstruction.
Autorzy:
Shen L; Stanford University, Stanford, CA, 94305, USA. Electronic address: .
Zhao W; Stanford University, Stanford, CA, 94305, USA. Electronic address: .
Capaldi D; Stanford University, Stanford, CA, 94305, USA. Electronic address: .
Pauly J; Stanford University, Stanford, CA, 94305, USA. Electronic address: .
Xing L; Stanford University, Stanford, CA, 94305, USA. Electronic address: .
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Źródło:
Computers in biology and medicine [Comput Biol Med] 2022 Sep; Vol. 148, pp. 105710. Date of Electronic Publication: 2022 Jun 06.
Typ publikacji:
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
MeSH Terms:
Deep Learning*
Algorithms ; Cone-Beam Computed Tomography ; Image Processing, Computer-Assisted ; Imaging, Three-Dimensional
Czasopismo naukowe
Tytuł:
The effect of a deep-learning tool on dentists' performances in detecting apical radiolucencies on periapical radiographs.
Autorzy:
Hamdan MH; Department of General Dental Sciences, Marquette University School of Dentistry, Milwaukee, WI, United States.
Tuzova L; Denti.AI Technology Inc, Toronto, Canada.; Georgia Institute of Technology, Atlanta, United States.
Mol A; Division of Diagnostic Sciences, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, United States.
Tawil PZ; Division of Comprehensive Oral Health, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, United States.
Tuzoff D; Denti.AI Technology Inc, Toronto, Canada.
Tyndall DA; Division of Diagnostic Sciences, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, United States.
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Źródło:
Dento maxillo facial radiology [Dentomaxillofac Radiol] 2022 Sep 01; Vol. 51 (7), pp. 20220122. Date of Electronic Publication: 2022 Sep 12.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Tooth, Nonvital*/diagnostic imaging
Cone-Beam Computed Tomography/methods ; Dentists ; Humans ; Radiography
Czasopismo naukowe
Tytuł:
Deep learning system for paddy plant disease detection and classification.
Autorzy:
Haridasan A; Department of Computer Science and Engineering, Indian Institute of Information Technology, Kottayam, Kerala, India.
Thomas J; Department of Computer Science and Engineering, Indian Institute of Information Technology, Kottayam, Kerala, India.
Raj ED; Department of Computer Science and Engineering, Indian Institute of Information Technology, Kottayam, Kerala, India. .
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Źródło:
Environmental monitoring and assessment [Environ Monit Assess] 2022 Nov 18; Vol. 195 (1), pp. 120. Date of Electronic Publication: 2022 Nov 18.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Environmental Monitoring ; Plant Diseases ; Neural Networks, Computer ; Crops, Agricultural
Czasopismo naukowe
Tytuł:
Detection of K-complexes in EEG waveform images using faster R-CNN and deep transfer learning.
Autorzy:
Khasawneh N; Department of Software Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan. .
Fraiwan M; Department of Computer Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
Fraiwan L; Department of Electrical and Computer Engineering, Abu Dhabi University, Abu Dhabi, UAE.; Department of Biomedical Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid, 22110, Jordan.
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Źródło:
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2022 Nov 17; Vol. 22 (1), pp. 297. Date of Electronic Publication: 2022 Nov 17.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Neural Networks, Computer ; Electroencephalography ; Polysomnography ; Brain
Czasopismo naukowe
Tytuł:
Radiation pneumonitis prediction after stereotactic body radiation therapy based on 3D dose distribution: dosiomics and/or deep learning-based radiomics features.
Autorzy:
Huang Y; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.; Department of Nuclear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, China.; Key Laboratory of Nuclear Physics and Ion-Beam Application (MOE), Fudan University, Shanghai, 200433, China.
Feng A; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Lin Y; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Gu H; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Chen H; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Wang H; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Shao Y; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Duan Y; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.; Department of Nuclear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, China.
Zhuo W; Department of Nuclear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, China.; Key Laboratory of Nuclear Physics and Ion-Beam Application (MOE), Fudan University, Shanghai, 200433, China.
Xu Z; Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China. .
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Źródło:
Radiation oncology (London, England) [Radiat Oncol] 2022 Nov 17; Vol. 17 (1), pp. 188. Date of Electronic Publication: 2022 Nov 17.
Typ publikacji:
Randomized Controlled Trial; Journal Article
MeSH Terms:
Radiation Pneumonitis*/etiology
Radiosurgery*/adverse effects
Deep Learning*
Carcinoma, Non-Small-Cell Lung*/diagnostic imaging
Carcinoma, Non-Small-Cell Lung*/radiotherapy
Lung Neoplasms*/diagnostic imaging
Lung Neoplasms*/radiotherapy
Humans ; Retrospective Studies
Czasopismo naukowe
Tytuł:
Monkeypox Virus Detection and Deep Learning-based Approaches: Correspondence.
Autorzy:
Mungmunpuntipantip R; Private Academic Consultant, Bangkok, Thailand. .
Wiwanitkit V; University Centre for Research &, Development Department of Pharmaceutical Sciences, Chandigarh University Gharuan, Mohali, Punjab, India.
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Źródło:
Journal of medical systems [J Med Syst] 2022 Nov 17; Vol. 46 (12), pp. 98. Date of Electronic Publication: 2022 Nov 17.
Typ publikacji:
Letter
MeSH Terms:
Deep Learning*
Monkeypox*/diagnosis
Humans ; Monkeypox virus
Opinia redakcyjna
Tytuł:
Comparisons of deep learning and machine learning while using text mining methods to identify suicide attempts of patients with mood disorders.
Autorzy:
Wang X; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, 10 Xitoutiao, Youanmen Wai, Beijing 100069, China.
Wang C; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, 10 Xitoutiao, Youanmen Wai, Beijing 100069, China.
Yao J; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, 10 Xitoutiao, Youanmen Wai, Beijing 100069, China.
Fan H; Capital Medical University Affiliated Beijing Anding Hospital, Beijing, China.
Wang Q; Capital Medical University Affiliated Beijing Anding Hospital, Beijing, China.
Ren Y; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, 10 Xitoutiao, Youanmen Wai, Beijing 100069, China.
Gao Q; Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, 10 Xitoutiao, Youanmen Wai, Beijing 100069, China. Electronic address: .
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Źródło:
Journal of affective disorders [J Affect Disord] 2022 Nov 15; Vol. 317, pp. 107-113. Date of Electronic Publication: 2022 Aug 24.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Deep Learning*
Data Mining ; Female ; Humans ; Machine Learning ; Male ; Mood Disorders/diagnosis ; Suicide, Attempted
Czasopismo naukowe
Tytuł:
A fully automated deep learning pipeline for micro-CT-imaging-based densitometry of lung fibrosis murine models.
Autorzy:
Vincenzi E; Department of Computer Science, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy.; Camelot Biomedical System S.R.L, Via Al Ponte Reale 2/20, 16124, Genoa, Italy.
Fantazzini A; Camelot Biomedical System S.R.L, Via Al Ponte Reale 2/20, 16124, Genoa, Italy.
Basso C; Camelot Biomedical System S.R.L, Via Al Ponte Reale 2/20, 16124, Genoa, Italy.
Barla A; Department of Computer Science, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy.
Odone F; Department of Computer Science, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy.
Leo L; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Mecozzi L; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Mambrini M; Department of Veterinary Science, University of Parma, Parma, Italy.
Ferrini E; Department of Veterinary Science, University of Parma, Parma, Italy.
Sverzellati N; Department of Medicine and Surgery, University of Parma, Parma, Italy.
Stellari FF; Chiesi Farmaceutici S.P.A, Corporate Pre-Clinical Research and Development, Largo Belloli, 11/A, 43122, Parma, Italy. .
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Źródło:
Respiratory research [Respir Res] 2022 Nov 11; Vol. 23 (1), pp. 308. Date of Electronic Publication: 2022 Nov 11.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Pulmonary Fibrosis*/diagnostic imaging
Animals ; Mice ; X-Ray Microtomography ; Disease Models, Animal ; Densitometry
Czasopismo naukowe
Tytuł:
Sagittal intervertebral rotational motion: a deep learning-based measurement on flexion-neutral-extension cervical lateral radiographs.
Autorzy:
Yan Y; The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.; Rehabilitation Medicine Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
Zhang X; The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.; Rehabilitation Medicine Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
Meng Y; Rehabilitation Medicine Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
Shen Q; Rehabilitation Medicine Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China.
He L; Hangzhou Jianpei Technology Company Ltd, Hangzhou, 311200, Zhejiang, China.
Cheng G; Hangzhou Jianpei Technology Company Ltd, Hangzhou, 311200, Zhejiang, China.
Gong X; Rehabilitation Medicine Center, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China. .; Institute of Artificial Intelligence and Remote Imaging, Hangzhou Medical College, Hangzhou, 310014, Zhejiang, China. .
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Źródło:
BMC musculoskeletal disorders [BMC Musculoskelet Disord] 2022 Nov 08; Vol. 23 (1), pp. 967. Date of Electronic Publication: 2022 Nov 08.
Typ publikacji:
Journal Article
MeSH Terms:
Cervical Vertebrae*/diagnostic imaging
Deep Learning*
Humans ; Radiography ; Range of Motion, Articular ; Neck
Czasopismo naukowe
Tytuł:
Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis.
Autorzy:
Yang C; Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
Qin LH; Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
Xie YE; Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China.
Liao JY; Department of Radiology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China. .; Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Gaungxi Medical University), Ministry of Education, Nanning, 530021, Guangxi Zhuang Autonomous Region, People's Republic of China. .
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Źródło:
Radiation oncology (London, England) [Radiat Oncol] 2022 Nov 07; Vol. 17 (1), pp. 175. Date of Electronic Publication: 2022 Nov 07.
Typ publikacji:
Meta-Analysis; Systematic Review; Journal Article
MeSH Terms:
Deep Learning*
Uterine Cervical Neoplasms*/diagnostic imaging
Uterine Cervical Neoplasms*/radiotherapy
Female ; Humans ; Image Processing, Computer-Assisted/methods ; Tomography, X-Ray Computed/methods ; Pelvis
Czasopismo naukowe
Tytuł:
A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method.
Autorzy:
Sui A; School of Information Science and Technology, Fudan University, Shanghai 200438, China.
Deng Y; School of Information Science and Technology, Fudan University, Shanghai 200438, China.
Wang Y; School of Information Science and Technology, Fudan University, Shanghai 200438, China.
Yu J; School of Information Science and Technology, Fudan University, Shanghai 200438, China. Electronic address: .
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Źródło:
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2022 Nov 05; Vol. 280, pp. 121560. Date of Electronic Publication: 2022 Jun 25.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Algorithms ; Neural Networks, Computer ; Spectrum Analysis, Raman
Czasopismo naukowe
Tytuł:
COVID-19 classification using chest X-ray images based on fusion-assisted deep Bayesian optimization and Grad-CAM visualization.
Autorzy:
Hamza A; Department of Computer Science, HITEC University, Taxila, Pakistan.
Attique Khan M; Department of Computer Science, HITEC University, Taxila, Pakistan.
Wang SH; Department of Mathematics, University of Leicester, Leicester, United Kingdom.
Alhaisoni M; Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
Alharbi M; Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Hussein HS; Electrical Engineering Department, College of Engineering, King Khalid University, Abha, Saudi Arabia.; Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan, Egypt.
Alshazly H; Faculty of Computers and Information, South Valley University, Qena, Egypt.
Kim YJ; Department of Computer Science, Hanyang University, Seoul, South Korea.
Cha J; Department of Computer Science, Hanyang University, Seoul, South Korea.
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Źródło:
Frontiers in public health [Front Public Health] 2022 Nov 04; Vol. 10, pp. 1046296. Date of Electronic Publication: 2022 Nov 04 (Print Publication: 2022).
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
COVID-19*/diagnostic imaging
Humans ; X-Rays ; Bayes Theorem ; Neural Networks, Computer
Czasopismo naukowe
Tytuł:
PollenDetect: An Open-Source Pollen Viability Status Recognition System Based on Deep Learning Neural Networks.
Autorzy:
Tan Z; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
Yang J; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.; Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumchi 830091, China.
Li Q; Forestry and Fruit Tree Research Institute, Wuhan Academy of Agricultural Sciences, Wuhan 430075, China.
Su F; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
Yang T; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
Wang W; Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumchi 830091, China.
Aierxi A; Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumchi 830091, China.
Zhang X; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
Yang W; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
Kong J; Institute of Economic Crops, Xinjiang Academy of Agricultural Sciences, Urumchi 830091, China.
Min L; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China.
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Źródło:
International journal of molecular sciences [Int J Mol Sci] 2022 Nov 03; Vol. 23 (21). Date of Electronic Publication: 2022 Nov 03.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Plant Breeding ; Pollen ; Software ; Hot Temperature
Czasopismo naukowe
Tytuł:
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal.
Autorzy:
Masood F; School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.; The Department of Biomedical Engineering, Al-Khwarizmi College of Engineering, Baghdad University, Baghdad 10071, Iraq.
Sharma M; School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Mand D; School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Nesathurai S; The Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.; The Division of Physical Medicine and Rehabilitation, Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada.; The Department of Physical Medicine and Rehabilitation, Hamilton Health Sciences, St Joseph's Hamilton Healthcare, Hamilton, ON L8N 4A6, Canada.
Simmons HA; The Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.
Brunner K; The Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.
Schalk DR; The Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.
Sledge JB; The Lafayette Bone and Joint Clinic, Lafayette, LA 70508, USA.
Abdullah HA; School of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Nov 03; Vol. 22 (21). Date of Electronic Publication: 2022 Nov 03.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Spinal Cord Injuries*/diagnosis
Animals ; Electromyography/methods ; Neural Networks, Computer ; Machine Learning ; Macaca fascicularis
Czasopismo naukowe
Tytuł:
Gait Trajectory Prediction on an Embedded Microcontroller Using Deep Learning.
Autorzy:
Karakish M; Mechanical Engineering Department, College of Engineering and Technology, Cairo Campus, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Cairo 11757, Egypt.; Faculty of Engineering, German International University, Cairo, Egypt.
Fouz MA; Mechanical Engineering Department, College of Engineering and Technology, Cairo Campus, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Cairo 11757, Egypt.
ELsawaf A; Mechanical Engineering Department, College of Engineering and Technology, Cairo Campus, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Cairo 11757, Egypt.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Nov 03; Vol. 22 (21). Date of Electronic Publication: 2022 Nov 03.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Reproducibility of Results ; Gait ; Neural Networks, Computer ; Algorithms
Czasopismo naukowe

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