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Tytuł:
Self-Supervised Action Representation Learning Based on Asymmetric Skeleton Data Augmentation.
Autorzy:
Zhou H; College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China.; Key Laboratory of Sports Intelligence Reasearch, Hunan Normal University, Changsha 410081, China.
Li X; College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China.; Key Laboratory of Sports Intelligence Reasearch, Hunan Normal University, Changsha 410081, China.
Xu D; College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China.; Key Laboratory of Sports Intelligence Reasearch, Hunan Normal University, Changsha 410081, China.
Liu H; College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China.; Key Laboratory of Sports Intelligence Reasearch, Hunan Normal University, Changsha 410081, China.
Guo J; Key Laboratory of Sports Intelligence Reasearch, Hunan Normal University, Changsha 410081, China.; College of Physical Culture, Hunan Normal University, Changsha 410081, China.
Zhang Y; Key Laboratory of Sports Intelligence Reasearch, Hunan Normal University, Changsha 410081, China.; College of Physical Culture, Hunan Normal University, Changsha 410081, China.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Nov 20; Vol. 22 (22). Date of Electronic Publication: 2022 Nov 20.
Typ publikacji:
Journal Article
MeSH Terms:
Machine Learning*
Problem-Based Learning*
Learning ; Skeleton
Czasopismo naukowe
Tytuł:
Adversarial deep evolutionary learning for drug design.
Autorzy:
Abouchekeir S; Department of Computer Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, L2S 3A1, Ontario, Canada. Electronic address: .
Vu A; Department of Computer Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, L2S 3A1, Ontario, Canada. Electronic address: .
Mukaidaisi M; Department of Computer Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, L2S 3A1, Ontario, Canada. Electronic address: .
Grantham K; Department of Computer Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, L2S 3A1, Ontario, Canada. Electronic address: .
Tchagang A; Digital Technologies Research Centre, National Research Council Canada, 1200 Montreal Road, Ottawa, K1A 0R6, Ontario, Canada. Electronic address: .
Li Y; Department of Computer Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, L2S 3A1, Ontario, Canada. Electronic address: .
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Źródło:
Bio Systems [Biosystems] 2022 Dec; Vol. 222, pp. 104790. Date of Electronic Publication: 2022 Oct 11.
Typ publikacji:
Journal Article
MeSH Terms:
Neural Networks, Computer*
Machine Learning*
Drug Design ; Artificial Intelligence ; Learning
Czasopismo naukowe
Tytuł:
Exploring an online method of measuring implicit sequence-learning consciousness.
Autorzy:
Lu F; School of Education Science, Taizhou University, Taizhou, China.
Huang C; Jiangsu Educational Press Group, Nanjing, China.
Zhu C; Department of Psychology, Soochow University, Suzhou, China.
He Y; School of Educational Science, Yangzhou University, Yangzhou, China.
Shu D; School of Educational Science, Yangzhou University, Yangzhou, China.
Liu D; School of Educational Science, Yangzhou University, Yangzhou, China. .; Ren Ai Street #199, Suzhou, 215123, China. .
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Źródło:
Experimental brain research [Exp Brain Res] 2022 Dec; Vol. 240 (12), pp. 3141-3152. Date of Electronic Publication: 2022 Oct 14.
Typ publikacji:
Journal Article
MeSH Terms:
Consciousness*/physiology
Serial Learning*/physiology
Task Performance and Analysis*
Humans ; Cues ; Learning/physiology ; Reaction Time/physiology ; Internet ; Students
Czasopismo naukowe
Tytuł:
Co-design and delivery of a relational learning programme for nursing students and young people with severe and complex learning disabilities.
Autorzy:
Nash-Patel T; Kingston University & St George's University of London, Heritage2Health, United Kingdom. Electronic address: .
Morrow E; Research Support NI, Northern Ireland, United Kingdom. Electronic address: .
Paliokosta P; Inclusive Education and Special Educational Needs, Inclusion and Social Justice Special Interest Group, Kingston University & St George's University of London, United Kingdom. Electronic address: .
Dundas J; Kingston University & St George's University of London, Heritage2Health, United Kingdom. Electronic address: .
O'Donoghue B; Brighton, East Sussex, United Kingdom.
Anderson E; StoryAID, StoryAidEU, United Kingdom. Electronic address: .
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Źródło:
Nurse education today [Nurse Educ Today] 2022 Dec; Vol. 119, pp. 105548. Date of Electronic Publication: 2022 Sep 14.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Students, Nursing*
Learning Disabilities*
Humans ; Adolescent ; Child ; State Medicine ; Learning ; Program Development
Czasopismo naukowe
Tytuł:
DL 101: Basic introduction to deep learning with its application in biomedical related fields.
Autorzy:
Zhan T; Data and Statistical Sciences, AbbVie Inc., North Chicago, Illinois, USA.
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Źródło:
Statistics in medicine [Stat Med] 2022 Nov 20; Vol. 41 (26), pp. 5365-5378. Date of Electronic Publication: 2022 Aug 30.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Neural Networks, Computer ; Machine Learning
Czasopismo naukowe
Tytuł:
Machine Learning for Industry 4.0: A Systematic Review Using Deep Learning-Based Topic Modelling.
Autorzy:
Mazzei D; Department of Computer Science, University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa, Italy.
Ramjattan R; Department of Computer Science, University of Pisa, Largo B. Pontecorvo 3, 56127 Pisa, Italy.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Nov 09; Vol. 22 (22). Date of Electronic Publication: 2022 Nov 09.
Typ publikacji:
Systematic Review; Journal Article; Review
MeSH Terms:
Deep Learning*
Machine Learning ; Industry
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:
Data-driven predictive modeling of PM 2.5 concentrations using machine learning and deep learning techniques: a case study of Delhi, India.
Autorzy:
Masood A; Department of Civil Engineering, Jamia Millia Islamia University, New Delhi, 110025, India. .
Ahmad K; Department of Civil Engineering, Jamia Millia Islamia University, New Delhi, 110025, India.
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Źródło:
Environmental monitoring and assessment [Environ Monit Assess] 2022 Nov 03; Vol. 195 (1), pp. 60. Date of Electronic Publication: 2022 Nov 03.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Air Pollutants*/analysis
Air Pollution*/analysis
Benzene/analysis ; Environmental Monitoring/methods ; Machine Learning ; Particulate Matter/analysis
Czasopismo naukowe
Tytuł:
Artificial intelligence, machine learning and deep learning in musculoskeletal imaging: Current applications.
Autorzy:
D'Angelo T; Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy.; Department of Radiology and Nuclear Medicine, Rotterdam, Netherlands.
Caudo D; Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy.; Department or Radiology, IRRCS Centro Neurolesi 'Bonino Pulejo', Messina, Italy.
Blandino A; Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy.
Albrecht MH; Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Vogl TJ; Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Gruenewald LD; Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Gaeta M; Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy.
Yel I; Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Koch V; Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Martin SS; Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Lenga L; Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
Muscogiuri G; School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.; Department of Radiology, IRCCS Istituto Auxologico Italiano, San Luca Hospital, Milan, Italy.
Sironi S; School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy.; Department of Radiology, ASST Papa Giovanni XXIII Hospital, Bergamo, Italy.
Mazziotti S; Department of Biomedical Sciences and Morphological and Functional Imaging, University Hospital Messina, Messina, Italy.
Booz C; Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany.
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Źródło:
Journal of clinical ultrasound : JCU [J Clin Ultrasound] 2022 Nov; Vol. 50 (9), pp. 1414-1431. Date of Electronic Publication: 2022 Sep 07.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Deep Learning*
Musculoskeletal System*/diagnostic imaging
Humans ; Artificial Intelligence ; Machine Learning ; Image Processing, Computer-Assisted
Czasopismo naukowe
Tytuł:
Application of deep machine learning for the radiographic diagnosis of periodontitis.
Autorzy:
Chang J; Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA. .
Chang MF; Institute of Computational Intelligence, National Yangming Chiaotung University, Taipei, Taiwan.; Department of Computer Science, National Yangming Chiaotung University, Taipei, Taiwan.
Angelov N; Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
Hsu CY; Institute of Computational Intelligence, National Yangming Chiaotung University, Taipei, Taiwan.
Meng HW; Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
Sheng S; Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
Glick A; Department of General Practice and Dental Public Health, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
Chang K; Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
He YR; Institute of Computational Intelligence, National Yangming Chiaotung University, Taipei, Taiwan.
Lin YB; Institute of Computational Intelligence, National Yangming Chiaotung University, Taipei, Taiwan.; Department of Computer Science, National Yangming Chiaotung University, Taipei, Taiwan.
Wang BY; Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
Ayilavarapu S; Department of Periodontics and Dental Hygiene, The University of Texas Health Science Center at Houston School of Dentistry, Houston, TX, USA.
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Źródło:
Clinical oral investigations [Clin Oral Investig] 2022 Nov; Vol. 26 (11), pp. 6629-6637. Date of Electronic Publication: 2022 Jul 26.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Periodontitis*/diagnostic imaging
Alveolar Bone Loss*/diagnostic imaging
Humans ; Machine Learning ; Radiography
Czasopismo naukowe
Tytuł:
In silico prediction of chemical aquatic toxicity by multiple machine learning and deep learning approaches.
Autorzy:
Xu M; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
Yang H; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
Liu G; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
Tang Y; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
Li W; Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai, China.
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Źródło:
Journal of applied toxicology : JAT [J Appl Toxicol] 2022 Nov; Vol. 42 (11), pp. 1766-1776. Date of Electronic Publication: 2022 Jun 26.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Cyprinidae*
Deep Learning*
Animals ; Ecosystem ; Lethal Dose 50 ; Machine Learning
Czasopismo naukowe
Tytuł:
Interpreting mental state decoding with deep learning models.
Autorzy:
Thomas AW; Stanford Data Science, Stanford University, Stanford, CA, USA; Department of Psychology, Stanford University, Stanford, CA, USA. Electronic address: .
Ré C; Department of Computer Science, Stanford University, Stanford, CA, USA.
Poldrack RA; Stanford Data Science, Stanford University, Stanford, CA, USA; Department of Psychology, Stanford University, Stanford, CA, USA.
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Źródło:
Trends in cognitive sciences [Trends Cogn Sci] 2022 Nov; Vol. 26 (11), pp. 972-986.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Artificial Intelligence*
Brain Mapping*
Deep Learning*
Brain ; Humans ; Machine Learning ; Neuroimaging ; Reproducibility of Results
Czasopismo naukowe
Tytuł:
Predicting Chemical Carcinogens Using a Hybrid Neural Network Deep Learning Method.
Autorzy:
Limbu S; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA.
Dakshanamurthy S; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Oct 26; Vol. 22 (21). Date of Electronic Publication: 2022 Oct 26.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Humans ; Neural Networks, Computer ; Machine Learning ; Carcinogens/toxicity ; Carcinogens/chemistry ; Support Vector Machine
Czasopismo naukowe
Tytuł:
Network Threat Detection Using Machine/Deep Learning in SDN-Based Platforms: A Comprehensive Analysis of State-of-the-Art Solutions, Discussion, Challenges, and Future Research Direction.
Autorzy:
Ahmed N; School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia.
Ngadi AB; School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia.
Sharif JM; School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia.
Hussain S; School of Digital Science, University Brunei Darussalam, Jalan Tungku Link, Gadong BE1410, Brunei.
Uddin M; College of Computing and Information Technology, University of Doha For Science and Technology, Doha 24449, Qatar.
Rathore MS; Department of Computer Science, Capital University of Science and Technology, Islamabad 44000, Pakistan.
Iqbal J; Department of Computer Science, Capital University of Science and Technology, Islamabad 44000, Pakistan.
Abdelhaq M; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Alsaqour R; Department of Information Technology, College of Computing and Informatics, Saudi Electronic University, Riyadh 93499, Saudi Arabia.
Ullah SS; Department of Information and Communication Technology, University of Agder (UiA), N-4898 Grimstad, Norway.
Zuhra FT; School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Johor, Malaysia.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Oct 17; Vol. 22 (20). Date of Electronic Publication: 2022 Oct 17.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Deep Learning*
Software ; Machine Learning ; Confidentiality
Czasopismo naukowe
Tytuł:
Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities.
Autorzy:
Aslam N; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Khan IU; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Bashamakh A; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Alghool FA; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Aboulnour M; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Alsuwayan NM; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Alturaif RK; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Brahimi S; Department of Computer Information Systems, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Aljameel SS; Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
Al Ghamdi K; Department of Physiology, College of Medicine, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Oct 16; Vol. 22 (20). Date of Electronic Publication: 2022 Oct 16.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Multiple Sclerosis*/diagnostic imaging
Deep Learning*
Humans ; Reproducibility of Results ; Machine Learning ; Magnetic Resonance Imaging
Czasopismo naukowe
Tytuł:
Effects of data quality and quantity on deep learning for protein-ligand binding affinity prediction.
Autorzy:
Fan FJ; School of Health, Medical and Applied Sciences, Central Queensland University, Bundaberg, Queensland 4670, Australia.
Shi Y; Institute for Glycomics, Griffith University, Southport, Queensland 4222, Australia. Electronic address: .
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Źródło:
Bioorganic & medicinal chemistry [Bioorg Med Chem] 2022 Oct 15; Vol. 72, pp. 117003. Date of Electronic Publication: 2022 Sep 09.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Deep Learning*
Data Accuracy ; Ligands ; Machine Learning ; Protein Binding ; Proteins/metabolism
Czasopismo naukowe
Tytuł:
EnsembleSplice: ensemble deep learning model for splice site prediction.
Autorzy:
Akpokiro V; Department of Computer Science, University of Colorado, Colorado Springs, CO, 80918, USA.
Martin T; Department of Mathematics, Oberlin College, Oberlin, OH, 44074, USA.
Oluwadare O; Department of Computer Science, University of Colorado, Colorado Springs, CO, 80918, USA. .
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Źródło:
BMC bioinformatics [BMC Bioinformatics] 2022 Oct 06; Vol. 23 (1), pp. 413. Date of Electronic Publication: 2022 Oct 06.
Typ publikacji:
Journal Article
MeSH Terms:
Deep Learning*
Genomics ; Humans ; Machine Learning ; Neural Networks, Computer ; Reproducibility of Results
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:
Dual-level diagnostic feature learning with recurrent neural networks for treatment sequence recommendation.
Autorzy:
Min X; School of Computer Science and Engineering, Northeastern University, Shenyang, 110000, China. Electronic address: .
Li W; School of Computer Science and Engineering, Northeastern University, Shenyang, 110000, China; Key Laboratory of Intelligent Computing in Medical Image (MIIC), Northeastern University, Ministry of Education, Shenyang, 110000, China. Electronic address: .
Yang J; School of Computer Science and Engineering, Northeastern University, Shenyang, 110000, China. Electronic address: .
Xie W; School of Computer Science and Engineering, Northeastern University, Shenyang, 110000, China. Electronic address: .
Zhao D; School of Computer Science and Engineering, Northeastern University, Shenyang, 110000, China; Key Laboratory of Intelligent Computing in Medical Image (MIIC), Northeastern University, Ministry of Education, Shenyang, 110000, China. Electronic address: .
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Źródło:
Journal of biomedical informatics [J Biomed Inform] 2022 Oct; Vol. 134, pp. 104165. Date of Electronic Publication: 2022 Aug 28.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Machine Learning*
Neural Networks, Computer*
Electronic Health Records ; Humans ; Learning
Czasopismo naukowe
Tytuł:
A systematic review on machine learning and deep learning techniques in cancer survival prediction.
Autorzy:
P D; School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India.
C G; School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India. Electronic address: .
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Źródło:
Progress in biophysics and molecular biology [Prog Biophys Mol Biol] 2022 Oct; Vol. 174, pp. 62-71. Date of Electronic Publication: 2022 Aug 03.
Typ publikacji:
Journal Article; Review; Systematic Review
MeSH Terms:
Deep Learning*
Neoplasms*
Humans ; Machine Learning
Czasopismo naukowe

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