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


Starter badań:

Tytuł:
Image quality and lesion detectability of deep learning-accelerated T2-weighted Dixon imaging of the cervical spine.
Autorzy:
Seo G; Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea.
Lee SJ; Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea. .
Park DH; Department of Orthopaedic Surgery, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea.
Paeng SH; Department of Neurosurgery, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea.
Koerzdoerfer G; Siemens Healthcare GmbH, Erlangen, Germany.
Nickel MD; Siemens Healthcare GmbH, Erlangen, Germany.
Sung J; Siemens Healthineers Ltd, Seoul, Korea.
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Źródło:
Skeletal radiology [Skeletal Radiol] 2023 Dec; Vol. 52 (12), pp. 2451-2459. Date of Electronic Publication: 2023 May 26.
Typ publikacji:
Journal Article
MeSH Terms:
Magnetic Resonance Imaging*/methods
Deep Learning*
Humans ; Constriction, Pathologic/pathology ; Reproducibility of Results ; Cervical Vertebrae/diagnostic imaging ; Cervical Vertebrae/pathology
Czasopismo naukowe
Tytuł:
An integrated deep-learning model for smart waste classification.
Autorzy:
Mishra S; Department of Information Technology, Rajkiya Engineering College, Ambedkar Nagar, 224122, Uttar pradesh, India.
Yaduvanshi R; Department of of Computer Science and Engineering, Mahamaya Colege of Agriculture Engineering and Technology, Ambedkar Nagar, 224122, Uttar pradesh, India.
Rajpoot P; Department of Information Technology, Rajkiya Engineering College, Ambedkar Nagar, 224122, Uttar pradesh, India.
Verma S; Department of Information Technology, Rajkiya Engineering College, Ambedkar Nagar, 224122, Uttar pradesh, India.
Pandey AK; Department of Applied Science and Humanities, Rajkiya Engineering College, Ambedkar Nagar, 224122, Uttar pradesh, India. .
Pandey D; Department of Technical Education, IET, Dr. A. P. J. Abdul Kalam Technical University, Lucknow, 226021, Uttar pradesh, India.
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Źródło:
Environmental monitoring and assessment [Environ Monit Assess] 2024 Feb 17; Vol. 196 (3), pp. 279. Date of Electronic Publication: 2024 Feb 17.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Environmental Monitoring ; Environmental Health ; Natural Resources ; Population Growth
Czasopismo naukowe
Tytuł:
Automatic de-identification of French electronic health records: a cost-effective approach exploiting distant supervision and deep learning models.
Autorzy:
Azzouzi ME; Univ Rennes, INSERM, LTSI-UMR 1099, F-35000, Rennes, France. .
Coatrieux G; IMT Atlantique, INSERM, LATIM - UMR 1101, Brest, F-29238, France.
Bellafqira R; IMT Atlantique, INSERM, LATIM - UMR 1101, Brest, F-29238, France.
Delamarre D; CHU Rennes, Centre de Données Cliniques, Rennes, F-35000, France.
Riou C; CHU Rennes, Centre de Données Cliniques, Rennes, F-35000, France.
Oubenali N; Univ Rennes, INSERM, LTSI-UMR 1099, F-35000, Rennes, France.
Cabon S; Univ Rennes, INSERM, LTSI-UMR 1099, F-35000, Rennes, France.
Cuggia M; Univ Rennes, CHU Rennes, INSERM, LTSI-UMR 1099, F-35000, Rennes, France.
Bouzillé G; Univ Rennes, CHU Rennes, INSERM, LTSI-UMR 1099, F-35000, Rennes, France.
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Źródło:
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2024 Feb 16; Vol. 24 (1), pp. 54. Date of Electronic Publication: 2024 Feb 16.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Data Anonymization ; Electronic Health Records ; Cost-Benefit Analysis ; Confidentiality ; Natural Language Processing
Czasopismo naukowe
Tytuł:
A deep learning approach for projection and body-side classification in musculoskeletal radiographs.
Autorzy:
Fink A; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany. .
Tran H; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
Reisert M; Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.; Medical Physics, Department of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Rau A; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.; Department of Neuroradiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Bayer J; Department of Trauma and Orthopaedic Surgery, Schwarzwald-Baar Hospital, Villingen-Schwenningen, Germany.
Kotter E; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
Bamberg F; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
Russe MF; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Breisacher Str. 64, 79106, Freiburg, Germany.
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Źródło:
European radiology experimental [Eur Radiol Exp] 2024 Feb 14; Vol. 8 (1), pp. 23. Date of Electronic Publication: 2024 Feb 14.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Radiology*
Humans ; Artificial Intelligence ; Retrospective Studies ; Radiography
Czasopismo naukowe
Tytuł:
Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning.
Autorzy:
Paciorek AM; Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany. .
von Schacky CE; Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
Foreman SC; Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
Gassert FG; Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
Gassert FT; Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
Kirschke JS; TUM-Neuroimaging Center, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
Laugwitz KL; Department of Medicine I, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
Geith T; Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
Hadamitzky M; Department of Radiology, German Heart Center Munich, Technical University of Munich, Lazarettstraße 36, 80636, Munich, Germany.
Nadjiri J; Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
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Źródło:
BMC medical imaging [BMC Med Imaging] 2024 Feb 13; Vol. 24 (1), pp. 43. Date of Electronic Publication: 2024 Feb 13.
Typ publikacji:
Journal Article
MeSH Terms:
Gadolinium*
Deep Learning*
Humans ; Magnetic Resonance Imaging/methods ; Myocardium/pathology ; Contrast Media ; Pericardium
Czasopismo naukowe
Tytuł:
DeepVAQ : an adaptive deep learning for prediction of vascular access quality in hemodialysis patients.
Autorzy:
Julkaew S; College of Digital Science, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Wongsirichot T; Division of Computational Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla, Thailand. .
Damkliang K; Division of Computational Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
Sangthawan P; Department of Medicine, Division of Nephrology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand.
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Źródło:
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2024 Feb 12; Vol. 24 (1), pp. 45. Date of Electronic Publication: 2024 Feb 12.
Typ publikacji:
Journal Article
MeSH Terms:
Artificial Intelligence*
Deep Learning*
Humans ; Retrospective Studies ; Reproducibility of Results ; Bayes Theorem ; Renal Dialysis
Czasopismo naukowe
Tytuł:
TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.
Autorzy:
Wang Y; Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China.
Jiang Z; Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China.
Liang P; Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China.; Zhejiang Yangshengtang Institute of Natural Medication Co., Ltd, Hangzhou, China.
Liu Z; Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China.
Cai H; Center of Growth, Metabolism and Aging, Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China. .
Sun Q; Key Laboratory of Bio-Resources and Eco-Environment of the Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, China. .
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Źródło:
BMC genomics [BMC Genomics] 2024 Feb 12; Vol. 25 (1), pp. 167. Date of Electronic Publication: 2024 Feb 12.
Typ publikacji:
Journal Article
MeSH Terms:
Mycobacterium tuberculosis*/genetics
Deep Learning*
Tuberculosis*/microbiology
Tuberculosis, Multidrug-Resistant*/drug therapy
Humans ; Antitubercular Agents/pharmacology ; Antitubercular Agents/therapeutic use ; Mutation ; Microbial Sensitivity Tests
Czasopismo naukowe
Tytuł:
Deep learning in oral cancer- a systematic review.
Autorzy:
Warin K; Faculty of Dentistry, Thammasat University, Pathum Thani, Thailand. .
Suebnukarn S; Faculty of Dentistry, Thammasat University, Pathum Thani, Thailand.
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Źródło:
BMC oral health [BMC Oral Health] 2024 Feb 10; Vol. 24 (1), pp. 212. Date of Electronic Publication: 2024 Feb 10.
Typ publikacji:
Systematic Review; Journal Article
MeSH Terms:
Deep Learning*
Mouth Neoplasms*/diagnosis
Humans ; Quality of Life ; Clinical Decision-Making ; Databases, Factual
Czasopismo naukowe
Tytuł:
Application of deep learning for automated diagnosis and classification of hip dysplasia on plain radiographs.
Autorzy:
Magnéli M; Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA.; Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, MA, USA.; Karolinska Institutet, Department of Clinical Sciences, Danderyd Hospital, Stockholm, Sweden.
Borjali A; Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA.; Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, MA, USA.
Takahashi E; Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA.; Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, MA, USA.; Department of Orthopaedic Surgery, Kanazawa Medical University, Uchinada, Japan.
Axenhus M; Karolinska Institutet, Department of Clinical Sciences, Danderyd Hospital, Stockholm, Sweden. .; Department of Orthopaedic Surgery, Danderyd Hospital, Stockholm, Sweden. .
Malchau H; Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, MA, USA.; Department of Orthopaedic Surgery, Sahlgrenska University Hospital, Gothenburg, Sweden.
Moratoglu OK; Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA.; Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, MA, USA.
Varadarajan KM; Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA.
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Źródło:
BMC musculoskeletal disorders [BMC Musculoskelet Disord] 2024 Feb 09; Vol. 25 (1), pp. 117. Date of Electronic Publication: 2024 Feb 09.
Typ publikacji:
Multicenter Study; Journal Article
MeSH Terms:
Hip Dislocation*/diagnostic imaging
Hip Dislocation*/surgery
Deep Learning*
Hip Dislocation, Congenital*/diagnostic imaging
Hip Dislocation, Congenital*/surgery
Humans ; Pilot Projects ; Radiography ; Acetabulum/diagnostic imaging ; Acetabulum/surgery ; Retrospective Studies
Czasopismo naukowe
Tytuł:
Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques.
Autorzy:
Saggu S; Department of Health Research Methodology, Evidence & Impact, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4K1, Canada.
Daneshvar H; Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada.
Samavi R; Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada.
Pires P; Department of Psychiatry & Behavioural Neurosciences, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4K1, Canada.; McMaster Children's Hospital, Hamilton Health Sciences, 1200 Main St West, Hamilton, Ontario, L8N 3Z5, Canada.
Sassi RB; Department of Psychiatry, University of British Columbia, UBC Vancouver Campus, Vancouver, BC, V6T 2A1, Canada.
Doyle TE; Department of Electrical & Computer Engineering, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4K1, Canada.
Zhao J; McMaster Children's Hospital, Hamilton Health Sciences, 1200 Main St West, Hamilton, Ontario, L8N 3Z5, Canada.
Mauluddin A; McMaster Children's Hospital, Hamilton Health Sciences, 1200 Main St West, Hamilton, Ontario, L8N 3Z5, Canada.
Duncan L; Department of Psychiatry & Behavioural Neurosciences, McMaster University, 1280 Main St W, Hamilton, Ontario, L8S 4K1, Canada. .; McMaster Children's Hospital, Hamilton Health Sciences, 1200 Main St West, Hamilton, Ontario, L8N 3Z5, Canada. .
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Źródło:
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2024 Feb 08; Vol. 24 (1), pp. 42. Date of Electronic Publication: 2024 Feb 08.
Typ publikacji:
Journal Article
MeSH Terms:
Hospitalization*
Deep Learning*
Child ; Humans ; Adolescent ; Outpatients ; Mental Health ; Canada ; Emergency Service, Hospital
Czasopismo naukowe
Tytuł:
Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images.
Autorzy:
Tayebi Arasteh S; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany. .
Misera L; Institute and Polyclinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, Technische Universität Dresden, Dresden, Germany.; Else Kröner Fresenius Center for Digital Health, Technische Universität Dresden, Dresden, Germany.
Kather JN; Else Kröner Fresenius Center for Digital Health, Technische Universität Dresden, Dresden, Germany.; Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany.; Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany.
Truhn D; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.
Nebelung S; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.
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Źródło:
European radiology experimental [Eur Radiol Exp] 2024 Feb 08; Vol. 8 (1), pp. 10. Date of Electronic Publication: 2024 Feb 08.
Typ publikacji:
Journal Article
MeSH Terms:
Artificial Intelligence*
Deep Learning*
Databases, Factual
Czasopismo naukowe
Tytuł:
Applied deep learning in neurosurgery: identifying cerebrospinal fluid (CSF) shunt systems in hydrocephalus patients.
Autorzy:
Rhomberg T; Department of Neurosurgery, Inselspital, University Hospital Bern, Bern, Switzerland. .; Department of Neurosurgery and Neurorestoration, Klinikum Klagenfurt Am Wörthersee, Klagenfurt, Austria. .
Trivik-Barrientos F; Department of Neurosurgery, Landesklinikum Wiener Neustadt, Wiener Neustadt, Austria.
Hakim A; Department of Neuroradiology, Inselspital, University Hospital Bern, Bern, Switzerland.
Raabe A; Department of Neurosurgery, Inselspital, University Hospital Bern, Bern, Switzerland.
Murek M; Department of Neurosurgery, Inselspital, University Hospital Bern, Bern, Switzerland.
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Źródło:
Acta neurochirurgica [Acta Neurochir (Wien)] 2024 Feb 07; Vol. 166 (1), pp. 69. Date of Electronic Publication: 2024 Feb 07.
Typ publikacji:
Journal Article
MeSH Terms:
Neurosurgery*
Deep Learning*
Hydrocephalus*/surgery
Humans ; Cerebrospinal Fluid Shunts ; Neurosurgical Procedures ; Ventriculoperitoneal Shunt/methods
Czasopismo naukowe
Tytuł:
Empowering PET: harnessing deep learning for improved clinical insight.
Autorzy:
Artesani A; Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Milan, Pieve Emanuele, 20090, Italy.
Bruno A; Department of Business, Law, Economics and Consumer Behaviour 'Carlo A. Ricciardi', IULM Libera Università Di Lingue E Comunicazione, Via P. Filargo 38, Milan, 20143, Italy.
Gelardi F; Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Milan, Pieve Emanuele, 20090, Italy. .; Vita-Salute San Raffaele University, Via Olgettina 58, Milan, 20132, Italy. .
Chiti A; Vita-Salute San Raffaele University, Via Olgettina 58, Milan, 20132, Italy.; Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Via Olgettina 60, Milan, 20132, Italy.
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Źródło:
European radiology experimental [Eur Radiol Exp] 2024 Feb 07; Vol. 8 (1), pp. 17. Date of Electronic Publication: 2024 Feb 07.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Deep Learning*
Radiology*
Humans ; Artificial Intelligence ; Positron-Emission Tomography ; Power, Psychological
Czasopismo naukowe
Tytuł:
Artifact suppression for breast specimen imaging in micro CBCT using deep learning.
Autorzy:
Aootaphao S; Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand. .; Medical Imaging System Research Team, Assistive Technology and Medical Devices Research Group, National Electronics and Computer Technology Center, National Science and Technology Development Agency, Pathum Thani, Thailand. .
Puttawibul P; Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
Thajchayapong P; National Science and Technology Development Agency, Pathum Thani, Thailand.
Thongvigitmanee SS; Medical Imaging System Research Team, Assistive Technology and Medical Devices Research Group, National Electronics and Computer Technology Center, National Science and Technology Development Agency, Pathum Thani, Thailand.
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Źródło:
BMC medical imaging [BMC Med Imaging] 2024 Feb 06; Vol. 24 (1), pp. 34. Date of Electronic Publication: 2024 Feb 06.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Spiral Cone-Beam Computed Tomography*
Humans ; Artifacts ; Image Processing, Computer-Assisted/methods ; Phantoms, Imaging ; Cone-Beam Computed Tomography/methods ; X-Ray Microtomography ; Algorithms
Czasopismo naukowe
Tytuł:
Comparison of Sysmex XN-V body fluid mode and deep-learning-based quantification with manual techniques for total nucleated cell count and differential count for equine bronchoalveolar lavage samples.
Autorzy:
Lapsina S; Clinical Laboratory, Department of Clinical Diagnostics and Services, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, CH-8057, Zurich, Switzerland. .
Riond B; Clinical Laboratory, Department of Clinical Diagnostics and Services, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, CH-8057, Zurich, Switzerland.
Hofmann-Lehmann R; Clinical Laboratory, Department of Clinical Diagnostics and Services, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, CH-8057, Zurich, Switzerland.
Stirn M; Clinical Laboratory, Department of Clinical Diagnostics and Services, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, CH-8057, Zurich, Switzerland.
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Źródło:
BMC veterinary research [BMC Vet Res] 2024 Feb 05; Vol. 20 (1), pp. 48. Date of Electronic Publication: 2024 Feb 05.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Body Fluids*
Animals ; Horses ; Cell Count/veterinary ; Lymphocytes ; Algorithms ; Leukocyte Count/veterinary ; Reproducibility of Results
Czasopismo naukowe
Tytuł:
A systematic analysis of deep learning in genomics and histopathology for precision oncology.
Autorzy:
Unger M; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany.
Kather JN; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany. jakob_.; Department of Medicine I, University Hospital Dresden, Dresden, Germany. jakob_.; Pathology & Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK. jakob_.; Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany. jakob_.
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Źródło:
BMC medical genomics [BMC Med Genomics] 2024 Feb 05; Vol. 17 (1), pp. 48. Date of Electronic Publication: 2024 Feb 05.
Typ publikacji:
Review; Journal Article
MeSH Terms:
Neoplasms*/genetics
Deep Learning*
Humans ; Precision Medicine ; Genomics ; Mutation
Czasopismo naukowe
Tytuł:
Deep learning algorithm-based multimodal MRI radiomics and pathomics data improve prediction of bone metastases in primary prostate cancer.
Autorzy:
Zhang YF; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China.
Zhou C; The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Guo S; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China.
Wang C; The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Yang J; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China.
Yang ZJ; The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Wang R; The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.; Department of Nuclear Medicine, Gansu Provincial Hospital, Lanzhou, 730000, China.
Zhang X; The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
Zhou FH; The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China. ldyy_.; The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China. ldyy_.; Department of Urology, Gansu Provincial Hospital, Lanzhou, 730000, China. ldyy_.
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Źródło:
Journal of cancer research and clinical oncology [J Cancer Res Clin Oncol] 2024 Feb 05; Vol. 150 (2), pp. 78. Date of Electronic Publication: 2024 Feb 05.
Typ publikacji:
Randomized Controlled Trial; Journal Article
MeSH Terms:
Deep Learning*
Bone Neoplasms*/diagnostic imaging
Prostatic Neoplasms*/diagnostic imaging
Male ; Humans ; Radiomics ; Magnetic Resonance Imaging ; Algorithms ; Retrospective Studies
Czasopismo naukowe
Tytuł:
Monitoring carbon emissions using deep learning and statistical process control: a strategy for impact assessment of governments' carbon reduction policies.
Autorzy:
Ezenkwu CP; School of Creative and Cultural Business, Robert Gordon University, Aberdeen, UK. .
Cannon S; School of Creative and Cultural Business, Robert Gordon University, Aberdeen, UK.
Ibeke E; School of Creative and Cultural Business, Robert Gordon University, Aberdeen, UK.
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Źródło:
Environmental monitoring and assessment [Environ Monit Assess] 2024 Feb 03; Vol. 196 (3), pp. 231. Date of Electronic Publication: 2024 Feb 03.
Typ publikacji:
Journal Article
MeSH Terms:
Air Pollutants*/analysis
Deep Learning*
Humans ; Carbon Dioxide/analysis ; Carbon/analysis ; Artificial Intelligence ; Environmental Monitoring ; Government ; Policy
Czasopismo naukowe
Tytuł:
deepPGSegNet: MRI-based pituitary gland segmentation using deep learning.
Autorzy:
Choi US; Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation, Daegu, Republic of Korea.
Sung YW; Kansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.
Ogawa S; Kansei Fukushi Research Institute, Tohoku Fukushi University, Sendai, Japan.
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Źródło:
Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2024 Feb 02; Vol. 15, pp. 1338743. Date of Electronic Publication: 2024 Feb 02 (Print Publication: 2024).
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/methods ; Research Design ; Pituitary Gland/diagnostic imaging
Czasopismo naukowe
Tytuł:
Utilizing 3D Point Cloud Technology with Deep Learning for Automated Measurement and Analysis of Dairy Cows.
Autorzy:
Lee JG; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
Lee SS; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
Alam M; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
Lee SM; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
Seong HS; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
Park MN; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
Han S; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
Nguyen HP; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
Baek MK; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
Phan AT; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
Dang CG; National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Chungcheongnam-do, Republic of Korea.
Nguyen DT; ZOOTOS Co., Ltd., R&D Center, Anyang 14118, Gyeonggi-do, Republic of Korea.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2024 Feb 02; Vol. 24 (3). Date of Electronic Publication: 2024 Feb 02.
Typ publikacji:
Journal Article
MeSH Terms:
Cloud Computing*
Deep Learning*
Female ; Cattle ; Animals ; Reproducibility of Results ; Dairying/methods ; Technology
Czasopismo naukowe

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