박사

자기 치료 로봇 구동을 위한 LabVIEW 시뮬레이션 및 Deep Learning 기반의 스마트 전자기 제어 시스템 연구

논문상세정보
' 자기 치료 로봇 구동을 위한 LabVIEW 시뮬레이션 및 Deep Learning 기반의 스마트 전자기 제어 시스템 연구' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • Artificial intelligence
  • Datasets
  • Deep learning
  • Drug delivery
  • Electromagnetic auto Manipulation
  • Magnetic robotics
  • NI-Vision
  • Neural Network
  • Pondermotive force
  • Superparamagnetic
  • Trajectory planning path
  • Treatment robotics
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
2,107 0

0.0%

' 자기 치료 로봇 구동을 위한 LabVIEW 시뮬레이션 및 Deep Learning 기반의 스마트 전자기 제어 시스템 연구' 의 참고문헌

  • Z. Zhang, J. Ma, S. Liu, X. Liu, X. Yan, T. Niu, C. Li, Q. Li, C. Wang, C. Meng, Fully-covered metallic stenting in an infant with tracheoesophageal fistula due to button battery ingestion, International Journal of Pediatric Otorhinolaryngology 95 (2017) 80-83.
  • Z. Guo, X. Li, H. Huang, N. Guo, Q. Li, Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes, CoRR abs/1711.00049 (2017).
  • Y.P. Chen, Y. Li, G. Wang, An Enhanced Region Proposal Network for object detection using deep learning method, PloS one 13(9) (2018) e0203897-e0203897.
  • Y. Zhang, J. Yu, L. Zhang, J. Cai, D. Cai, C. Lv, Enhanced anti-tumor effects of doxorubicin on glioma by entrapping in polybutylcyanoacrylate nanoparticles, Tumor Biology 37(2) (2016) 2703-2708.
  • Y. Tu, F. Peng, D.A. Wilson, Motion Manipulation of Micro- and Nanomotors, Advanced Materials 29(39) (2017) 1701970-n/a.
  • Y. Noh, M. Segawa, K. Sato, W. Chunbao, H. Ishii, J. Solis, A. Takanishi, A. Katsumata, Y. Iida, Development of a robot which can simulate swallowing of food boluses with various properties for the study of rehabilitation of swallowing disorders, 2011 IEEE International Conference on Robotics and Automation, 2011, pp. 4676-4681.
  • Y. Ido, Y.-H. Li, H. Tsutsumi, H. Sumiyoshi, C.-Y. Chen, Magnetic microchains and microswimmers in an oscillating magnetic field, Biomicrofluidics 10(1) (2016) 011902-011902.
  • X. Gu, L. Liu, Z. Ni, J. Cheng, Z. Long, Investigation on the design and experimental application of novel fatigue testing device for esophagus stent, 2013 IEEE International Conference on Mechatronics and Automation, 2013, pp. 407-411.
  • W. Yuan, Y. Mo, S. Wang, E.H. Adelson, Active Clothing Material Perception using Tactile Sensing and Deep Learning, CoRR abs/1711.00574 (2017).
  • V. Nagaraja, M.R. Cox, G.D. Eslick, Safety and efficacy of esophageal stents preceding or during neoadjuvant chemotherapy for esophageal cancer: a systematic review and meta-analysis, Journal of Gastrointestinal Oncology 5(2) (2014) 119-126.
  • V. Mody Vicky, A. Singh, B. Wesley, Basics of magnetic nanoparticles for their application in the field of magnetic fluid hyperthermia, European Journal of Nanomedicine, 2013, p. 11.
  • V. Jain, S. Jain, S.C. Mahajan, Nanomedicines based drug delivery systems for anti-cancer targeting and treatment, Current drug delivery 12(2) (2015) 177-91.
  • V. Chaudhary, S. Jangra, N.R. Yadav, Nanotechnology based approaches for detection and delivery of microRNA in healthcare and crop protection, Journal of nanobiotechnology 16(1) (2018) 40-40.
  • U.K. Cheang, F. Meshkati, H. Kim, K. Lee, H.C. Fu, M.J. Kim, Versatile microrobotics using simple modular subunits, 6 (2016) 30472.
  • U. Aebi, P. Gehr, Swiss National Research Programme "Opportunities and Risks of Nanomaterials" (NRP 64): key findings, Journal of nanobiotechnology 15(1) (2017) 47-47.
  • T.R. Mauldin, M.E. Canby, V. Metsis, A.H.H. Ngu, C.C. Rivera, SmartFall: A Smartwatch-Based Fall Detection System Using Deep Learning, Sensors (Basel, Switzerland) 18(10) (2018) 3363.
  • T.H. Kim, N. Patel, M. Ledgerwood-Lee, R.K. Mittal, Esophageal contractions in type 3 achalasia esophagus: simultaneous or peristaltic?, American Journal of Physiology - Gastrointestinal and Liver Physiology 310(9) (2016) G689-G695.
  • T. Yuan, R. Zheng, J. Yu, L. Edmonds, W. Wu, J. Cao, F. Gao, Y. Zhu, Y. Cheng, W. Cui, Fabrication and evaluation of polymer-based esophageal stents for benign esophagus stricture insertion, RSC Advances 6(20) (2016) 16891-16898.
  • T. Ye, B. Wang, P. Song, J. Li, Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode, Sensors (Basel, Switzerland) 18(6) (2018) 1916.
  • T. Szkodny, The Algorithm Camera Computing the Object Location, in: J. Lee, M.C. Lee, H. Liu, J.-H. Ryu (Eds.), Intelligent Robotics and Applications: 6th International Conference, ICIRA 2013, Busan, South Korea, September 25-28, 2013, Proceedings, Part I, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, pp. 637-648.
  • T. Ching, D.S. Himmelstein, B.K. Beaulieu-Jones, A.A. Kalinin, B.T. Do, G.P. Way, E. Ferrero, P.-M. Agapow, M. Zietz, M.M. Hoffman, W. Xie, G.L. Rosen, B.J. Lengerich, J. Israeli, J. Lanchantin, S. Woloszynek, A.E. Carpenter, A. Shrikumar, J. Xu, E.M. Cofer, C.A. Lavender, S.C. Turaga, A.M. Alexandari, Z. Lu, D.J. Harris, D. DeCaprio, Y. Qi, A. Kundaje, Y. Peng, L.K. Wiley, M.H.S. Segler, S.M. Boca, S.J. Swamidass, A. Huang, A. Gitter, C.S. Greene, Opportunities and obstacles for deep learning in biology and medicine, Journal of the Royal Society, Interface 15(141) (2018) 20170387.
  • T. Batgerel, A.R. Unnithan, C.-H. Park, C.S. Kim, Design and development of an electro magnetic manipulation system to actuate bioengineered magnetic micro/nanoparticles, Journal of Mechanical Science and Technology 32(4) (2018) 1693-1703.
  • S.-W. Hsieh, H.-S. Chen, Y.-T. Chen, K.-C. Hung, To characterize the incidence of airway misplacement of nasogastric tubes in anesthetized intubated patients by using a manometer technique, Journal of Clinical Monitoring and Computing 31(2) (2017) 443-448.
  • S. Yang, D.O. Schmidt, A. Khetan, F. Schrader, S. Jakobi, M. Homberger, M. Noyong, A. Paulus, H. Kungl, R.-A. Eichel, H. Pitsch, U. Simon, Electrochemical and Electronic Charge Transport Properties of Ni-Doped LiMn₂O₄ Spinel Obtained from Polyol-Mediated Synthesis, Materials (Basel, Switzerland) 11(5) (2018) 806.
  • S. Verma, R. Chevvuri, H. Sharma, Nanotechnology in dentistry: Unleashing the hidden gems, Journal of Indian Society of Periodontology 22(3) (2018) 196-200.
  • S. Sheckman, H. Kim, S. Manzoor, L.W. Rogowski, L. Huang, X. Zhang, A.T. Becker, M.J. Kim, Manipulation and control of microrobots using a novel permanent magnet stage, 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2017, pp. 692-696.
  • S. Sch rle, B.E. Kratochvil, S. Pan , M.A. Zeeshan, B.J. Nelson, Generating Magnetic Fields for Controlling Nanorobots in Medical Applications, in: C. Mavroidis, A. Ferreira (Eds.), Springer2013, p. 299.
  • S. Karagul, M.A. Yagci, C. Ara, A. Tardu, I. Ertugrul, S. Kirmizi, F. Sumer, Small bowel perforation due to a migrated esophageal stent: Report of a rare case and review of the literature, International Journal of Surgery Case Reports 11 (2015) 113-116.
  • S. Dirven, W. Xu, L.K. Cheng, J. Bronlund, Soft-Robotic Peristaltic Pumping Inspired by Esophageal Swallowing in Man, in: J.-H. Kim, E.T. Matson, H. Myung, P. Xu, F. Karray (Eds.), Robot Intelligence Technology and Applications 2: Results from the 2nd International Conference on Robot Intelligence Technology and Applications, Springer International Publishing, Cham, 2014, pp. 473-482.
  • S. Dirven, F. Chen, W. Xu, J.E. Bronlund, J. Allen, L.K. Cheng, Design and Characterization of a Peristaltic Actuator Inspired by Esophageal Swallowing, IEEE/ASME Transactions on Mechatronics 19(4) (2014) 1234-1242.
  • R.S.M. Rikken, R.J.M. Nolte, J.C. Maan, J.C.M. van Hest, D.A. Wilson, P.C.M. Christianen, Manipulation of micro- and nanostructure motion with magnetic fields, Soft Matter 10(9) (2014) 1295-1308.
  • R.M. Rockmore, Scattering of Electromagnetic Waves in a Spinor Formalism, Physical Review 147(4) (1966) 899-905.
  • R.G. Thomas, A.R. Unnithan, M.J. Moon, S.P. Surendran, T. Batgerel, C.H. Park, C.S. Kim, Y.Y. Jeong, Electromagnetic manipulation enabled calcium alginate Janus microsphere for targeted delivery of mesenchymal stem cells, International journal of biological macromolecules 110 (2018) 465-471.
  • R.D. Smolkin, Calculation of magnetic field strength and electromagnetic ponderomotive force of separators, IEEE Transactions on Magnetics 38(3) (2002) 1528-1533.
  • R. Guerchais, G. Scalet, A. Constantinescu, F. Auricchio, Micromechanical modeling for the probabilistic failure prediction of stents in high-cycle fatigue, International Journal of Fatigue 87 (2016) 405-417.
  • Q. Yu, S. Mulmi, Y. Liu, The Placement of Esophageal Stents in Different Esophageal Disease Related Conditions A Review, Open Journal of Gastroenterology Vol.06No.04 (2016) 10.
  • Q. Huang, F. Zhang, X. Li, Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey, BioMed research international 2018 (2018) 5137904-5137904.
  • Pu, #xe9, S. rtolas, E. Bajador, Pu, #xe9, J. rtolas, #xe9, A., #xf3, E. pez, E. Ibarz, L. Gracia, A. Herrera, Study of the Behavior of a Bell-Shaped Colonic Self-Expandable NiTi Stent under Peristaltic Movements, BioMed Research International 2013 (2013) 10.
  • P. Vlamos, K. Lefkimmiatis, C. Cocianu, L. State, Z. Luo, Artificial Intelligence Applications in Biomedicine, Advances in Artificial Intelligence 2013 (2013) 2.
  • P. Sharma, R. Kozarek, Role of Esophageal Stents in Benign and Malignant Diseases, Am J Gastroenterol 105(2) (2009) 258-273.
  • P. Sengar, P. Ju rez, A. Verdugo-Meza, D.L. Arellano, A. Jain, K. Chauhan, G.A. Hirata, P.G.J. Fournier, Development of a functionalized UV-emitting nanocomposite for the treatment of cancer using indirect photodynamic therapy, Journal of nanobiotechnology 16(1) (2018) 19-19.
  • P. Ryan, E. Diller, Five-degree-of-freedom magnetic control of micro-robots using rotating permanent magnets, 2016 IEEE International Conference on Robotics and Automation (ICRA), 2016, pp. 1731-1736.
  • P. He, R. Hong, H. Wang, C. Lu, Fatigue life analysis of slewing bearings in wind turbines, International Journal of Fatigue 111 (2018) 233-242.
  • P. Baldi, Deep Learning in Biomedical Data Science, Annual Review of Biomedical Data Science 1(1) (2018) 181-205.
  • O.V. Salata, Applications of nanoparticles in biology and medicine, Journal of Nanobiotechnology 2(1) (2004) 3.
  • N. Patel, Y. Jiang, R.K. Mittal, T.H. Kim, M. Ledgerwood, V. Bhargava, Circular and longitudinal muscles shortening indicates sliding patterns during peristalsis and transient lower esophageal sphincter relaxation, American Journal of Physiology - Gastrointestinal and Liver Physiology 309(5) (2015) G360-G367.
  • N. Holmes, J. Leggett, E. Boto, G. Roberts, R.M. Hill, T.M. Tierney, V. Shah, G.R. Barnes, M.J. Brookes, R. Bowtell, A bi-planar coil system for nulling background magnetic fields in scalp mounted magnetoencephalography, NeuroImage 181 (2018) 760-774.
  • M.J. Banner, C.G. Tams, N.R. Euliano, P.J. Stephan, T.J. Leavitt, A.D. Martin, N. Al-Rawas, A. Gabrielli, Real time noninvasive estimation of work of breathing using facemask leak-corrected tidal volume during noninvasive pressure support: validation study, Journal of Clinical Monitoring and Computing 30(3) (2016) 285-294.
  • M.D. Tehrani, M.O. Kim, J. Yoon, A Novel Electromagnetic Actuation System for Magnetic Nanoparticle Guidance in Blood Vessels, IEEE Transactions on Magnetics 50(7) (2014) 1-12.
  • M.A. Nicosia, J.G. Brasseur, J.-B. Liu, L.S. Miller, Local longitudinal muscle shortening of the human esophagus from high-frequency ultrasonography, American Journal of Physiology - Gastrointestinal and Liver Physiology 281(4) (2001) G1022-G1033.
  • M.A. Le n, J. R s nen, Neural network-based detection of esophageal intubation in anesthetized patients, Journal of Clinical Monitoring 12(2) (1996) 165-169.
  • M. Zhu, W. Xu, L.K. Cheng, Esophageal Peristaltic Control of a Soft-Bodied Swallowing Robot by the Central Pattern Generator, IEEE/ASME Transactions on Mechatronics 22(1) (2017) 91-98.
  • M. Xie, A. Shakoor, C. Wu, Manipulation of Biological Cells Using a Robot-Aided Optical Tweezers System, Micromachines 9(5) (2018) 245.
  • M. Westwood, T.R. Noel, R. Parker, The effect of poly-l-lysine structure on the pH response of polygalacturonic acid-based multilayers, Carbohydrate Polymers 94(1) (2013) 137-146.
  • M. Wei, S. Li, W. Le, Nanomaterials modulate stem cell differentiation: biological interaction and underlying mechanisms, Journal of nanobiotechnology 15(1) (2017) 75-75.
  • M. Racuciu, S. Miclaus, D. Creanga, On the thermal effect induced in tissue samples exposed to extremely low-frequency electromagnetic field, Journal of Environmental Health Science and Engineering 13(1) (2015) 85.
  • M. Garbey, R. Salmon, V. Fikfak, C.O. Clerc, Esophageal stent migration: Testing few hypothesis with a simplified mathematical model, Computers in biology and medicine 79 (2016) 259-265.
  • M. Fletcher, M. Biglarbegian, S. Neethirajan, Intelligent system design for bionanorobots in drug delivery, Cancer nanotechnology 4(4-5) (2013) 117-125.
  • M. Dadkhah, N. Kumar, J. Yoon, Design and Simulation of a 3D Actuation System for Magnetic Nano-Particles Delivery System, in: J. Lee, M.C. Lee, H. Liu, J.-H. Ryu (Eds.), Intelligent Robotics and Applications: 6th International Conference, ICIRA 2013, Busan, South Korea, September 25-28, 2013, Proceedings, Part I, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, pp. 177-187.
  • M. Czaplik, C.H. Antink, R. Rossaint, S. Leonhardt, Application of internal electrodes to the oesophageal and tracheal tube in an animal trial: evaluation of its clinical and technical potentiality in electrical impedance tomography, Journal of Clinical Monitoring and Computing 28(3) (2014) 299-308.
  • L.E. Aguilar, B. Tumurbaatar, A. Ghavaminejad, C.H. Park, C.S. Kim, Functionalized Non-vascular Nitinol Stent via Electropolymerized Polydopamine Thin Film Coating Loaded with Bortezomib Adjunct to Hyperthermia Therapy, Scientific Reports 7(1) (2017) 9432.
  • L.E. Aguilar, A.R. Unnithan, A. Amarjargal, A.P. Tiwari, S.T. Hong, C.H. Park, C.S. Kim, Electrospun polyurethane/Eudragit L100-55 composite mats for the pH dependent release of paclitaxel on duodenal stent cover application, International Journal of Pharmaceutics 478(1) (2015) 1-8.
  • L.E. Aguilar, A. GhavamiNejad, C.H. Park, C.S. Kim, On-demand drug release and hyperthermia therapy applications of thermoresponsive poly-(NIPAAm-co-HMAAm)/polyurethane core-shell nanofiber mat on non-vascular nitinol stents, Nanomedicine: Nanotechnology, Biology and Medicine 13(2) (2017) 527-538.
  • L. Yu, X. Shao, Y. Wei, K. Zhou, Intelligent Land-Vehicle Model Transfer Trajectory Planning Method Based on Deep Reinforcement Learning, Sensors (Basel, Switzerland) 18(9) (2018) 2905.
  • L. Agiotis, I. Theodorakos, S. Samothrakitis, S. Papazoglou, I. Zergioti, Y.S. Raptis, Magnetic manipulation of superparamagnetic nanoparticles in a microfluidic system for drug delivery applications, Journal of Magnetism and Magnetic Materials 401 (2016) 956-964.
  • K.S. Siddiqi, A. Husen, R.A.K. Rao, A review on biosynthesis of silver nanoparticles and their biocidal properties, Journal of nanobiotechnology 16(1) (2018) 14-14.
  • K.S. Dua, S.U. Latif, J.F. Yang, T.C. Fang, A. Khan, Y. Oh, Efficacy and safety of a new fully covered self-expandable non-foreshortening metal esophageal stent, Gastrointestinal Endoscopy 80(4) (2014) 577-585.
  • K.B. Parizi, D. Akin, H.S.P. Wong, Internalization of subcellular-scale microfabricated chips by healthy and cancer cells, PloS one 13(3) (2018) e0194712-e0194712.
  • J.U. Cho, S.H. Jin, X.D. Pham, J.W. Jeon, J.E. Byun, H. Kang, A Real-Time Object Tracking System Using a Particle Filter, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006, pp. 2822-2827.
  • J.G.S. Moo, C.C. Mayorga-Martinez, H. Wang, B. Khezri, W.Z. Teo, M. Pumera, Nano/Microrobots Meet Electrochemistry, Advanced Functional Materials 27(12) (2017) 1604759-n/a.
  • J.F. Durodola, S. Ramachandra, S. Gerguri, N.A. Fellows, Artificial neural network for random fatigue loading analysis including the effect of mean stress, International Journal of Fatigue 111 (2018) 321-332.
  • J. Yoo, E. Lee, H.Y. Kim, D.-h. Youn, J. Jung, H. Kim, Y. Chang, W. Lee, J. Shin, S. Baek, W. Jang, W. Jun, S. Kim, J. Hong, H.-J. Park, C.J. Lengner, S.H. Moh, Y. Kwon, J. Kim, Electromagnetized gold nanoparticles mediate direct lineage reprogramming into induced dopamine neurons in vivo for Parkinson's disease therapy, Nature Nanotechnology 12 (2017) 1006.
  • J. Wang, F. Liu, F. Tao, Q. Pan, Rationally Designed Self-Healing Hydrogel Electrolyte toward a Smart and Sustainable Supercapacitor, ACS Applied Materials & Interfaces 9(33) (2017) 27745-27753.
  • J. Song, H. Hu, C. Jian, K. Wu, X. Chen, New Generation of Gold Nanoshell-Coated Esophageal Stent: Preparation and Biomedical Applications, ACS Applied Materials & Interfaces 8(41) (2016) 27523-27529.
  • J. Rahmer, C. Stehning, B. Gleich, Remote magnetic actuation using a clinical scale system, PloS one 13(3) (2018) e0193546-e0193546.
  • J. Li, B. Esteban-Fern ndez de vila, W. Gao, L. Zhang, J. Wang, Micro/nanorobots for biomedicine: Delivery, surgery, sensing, and detoxification, Science Robotics 2(4) (2017).
  • J. Gjorgjieva, J. Berni, J.F. Evers, S. Eglen, Neural circuits for peristaltic wave propagation in crawling Drosophila larvae: analysis and modeling, Frontiers in Computational Neuroscience 7(24) (2013).
  • J. Fang, T. Wen, A wide linear range Eddy Current Displacement Sensor equipped with dual-coil probe applied in the Magnetic Suspension Flywheel, Sensors (Basel, Switzerland) 12(8) (2012) 10693-10706.
  • J. Estelrich, M.A. Busquets, Iron Oxide Nanoparticles in Photothermal Therapy, Molecules (Basel, Switzerland) 23(7) (2018) 1567.
  • H.C. Jan en, D.P. Warwas, D. Dahlhaus, J. Mei ner, P. Taptimthong, M. Kietzmann, P. Behrens, J. Reifenrath, N. Angrisani, In vitro and in vivo accumulation of magnetic nanoporous silica nanoparticles on implant materials with different magnetic properties, Journal of Nanobiotechnology 16(1) (2018) 96.
  • H.-B. Li, N. Lu, Q. Zhang, Y. Wang, D. Feng, T. Chen, S. Yang, Z. Duan, Z. Li, Y. Shi, W. Wang, W.-H. Wang, K. Jin, H. Liu, J. Ma, L. Gu, C. Nan, P. Yu, Electric-field control of ferromagnetism through oxygen ion gating, Nature communications 8(1) (2017) 2156-2156.
  • H. Wu, Y. Zhou, Gene Ontology (GO) Prediction using Machine Learning Methods, CoRR abs/1711.00001 (2017).
  • H. Kratz, M. Taupitz, A. Ariza de Schellenberger, O. Kosch, D. Eberbeck, S. Wagner, L. Trahms, B. Hamm, J. Schnorr, Novel magnetic multicore nanoparticles designed for MPI and other biomedical applications: From synthesis to first in vivo studies, PloS one 13(1) (2018) e0190214-e0190214.
  • H. Ezzaier, J.A. Marins, C. Claudet, G. Hemery, O. Sandre, P. Kuzhir, Kinetics of Aggregation and Magnetic Separation of Multicore Iron Oxide Nanoparticles: Effect of the Grafted Layer Thickness, Nanomaterials (Basel, Switzerland) 8(8) (2018) 623.
  • H. Ding, C. Shi, L. Ma, Z. Yang, M. Wang, Y. Wang, T. Chen, L. Sun, F. Toshio, Visual Servoing-Based Nanorobotic System for Automated Electrical Characterization of Nanotubes inside SEM, Sensors (Basel, Switzerland) 18(4) (2018) 1137.
  • H. Choi, S. Jeong, C. Lee, B.J. Park, S.Y. Ko, J.-O. Park, S. Park, Three-dimensional swimming tadpole mini-robot using three-axis Helmholtz coils, International Journal of Control, Automation and Systems 12(3) (2014) 662-669.
  • G.P. Zhang, M.S. Si, M. Murakami, Y.H. Bai, T.F. George, Generating high-order optical and spin harmonics from ferromagnetic monolayers, Nature communications 9(1) (2018) 3031-3031.
  • G. Del Fiol, M. Michelson, A. Iorio, C. Cotoi, R.B. Haynes, A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study, Journal of medical Internet research 20(6) (2018) e10281-e10281.
  • F.M. Weafer, M.S. Bruzzi, Micromechanical investigation into the effect of texture on the fatigue behaviour of superelastic nitinol, International Journal of Fatigue 93 (2016) 148-155.
  • F. Qiu, B.J. Nelson, Magnetic Helical Micro- and Nanorobots: Toward Their Biomedical Applications, Engineering 1(1) (2015) 021-026.
  • E. Maleki, O. Unal, K. Reza Kashyzadeh, Fatigue behavior prediction and analysis of shot peened mild carbon steels, International Journal of Fatigue 116 (2018) 48-67.
  • E. Gibson, W. Li, C. Sudre, L. Fidon, D.I. Shakir, G. Wang, Z. Eaton-Rosen, R. Gray, T. Doel, Y. Hu, T. Whyntie, P. Nachev, M. Modat, D.C. Barratt, S. Ourselin, M.J. Cardoso, T. Vercauteren, NiftyNet: a deep-learning platform for medical imaging, Computer methods and programs in biomedicine 158 (2018) 113-122.
  • E. Coballase-Urrutia, L. Navarro, J.L. Ortiz, L. Verdugo-D az, J.M. Gallardo, M.E. Hern ndez, F. Estrada-Rojo, Static Magnetic Fields Modulate the Response of Different Oxidative Stress Markers in a Restraint Stress Model Animal, BioMed research international 2018 (2018) 3960408-3960408.
  • D.P. Bhattarai, A.P. Tiwari, B. Maharjan, B. Tumurbaatar, C.H. Park, C.S. Kim, Sacrificial template-based synthetic approach of polypyrrole hollow fibers for photothermal therapy, Journal of colloid and interface science 534 (2019) 447-458.
  • D.J. Griffiths, Introduction to electrodynamics, 3rd ed., international ed ed., Pearson/Benjamin Cummings, San Francisco London, 2008.
  • D.A. Pelevina, V.A. Turkov, S.A. Kalmykov, V.A. Naletova, Motions of objects with magnetizable materials along a horizontal plane in a rotating magnetic field, Journal of Magnetism and Magnetic Materials 390 (2015) 20-25.
  • D.-W. Jang, S. Lee, J.-W. Park, D.-C. Baek, Failure detection technique under random fatigue loading by machine learning and dual sensing on symmetric structure, International Journal of Fatigue 114 (2018) 57-64.
  • D. Shukla, . Erkent, J. Piater, Learning Semantics of Gestural Instructions for Human-Robot Collaboration, Frontiers in neurorobotics 12 (2018) 7-7.
  • D. Shen, G. Wu, H.-I. Suk, Deep Learning in Medical Image Analysis, Annual review of biomedical engineering 19 (2017) 221-248.
  • D. Shen, G. Wu, H.-I. Suk, Deep Learning in Medical Image Analysis, Annual Review of Biomedical Engineering 19(1) (2017) 221-248.
  • D. Chang, M. Lim, J.A.C.M. Goos, R. Qiao, Y.Y. Ng, F.M. Mansfeld, M. Jackson, T.P. Davis, M. Kavallaris, Biologically Targeted Magnetic Hyperthermia: Potential and Limitations, Frontiers in pharmacology 9 (2018) 831-831.
  • C. Yu, J. Kim, H. Choi, J. Choi, S. Jeong, K. Cha, J.-o. Park, S. Park, Novel electromagnetic actuation system for three-dimensional locomotion and drilling of intravascular microrobot, Sensors and Actuators A: Physical 161(1) (2010) 297-304.
  • C. Park, C.C. Took, J.-K. Seong, Machine learning in biomedical engineering, Biomedical Engineering Letters 8(1) (2018) 1-3.
  • C. Kittel, Introduction to Solid State Physics, Wiley2004.
  • C. Hyunchul, C. Jongho, J. Gunhee, P. Jong-oh, P. Sukho, Two-dimensional actuation of a microrobot with a stationary two-pair coil system, Smart Materials and Structures 18(5) (2009) 055007.
  • C. Hu, S. Pan , B.J. Nelson, Soft Micro- and Nanorobotics, Annual Review of Control, Robotics, and Autonomous Systems 1(1) (2018) 53-75.
  • B.R. Matam, H. Duncan, Technical challenges related to implementation of a formula one real time data acquisition and analysis system in a paediatric intensive care unit, Journal of Clinical Monitoring and Computing (2017).
  • A.M. Tokmachev, D.V. Averyanov, O.E. Parfenov, A.N. Taldenkov, I.A. Karateev, I.S. Sokolov, O.A. Kondratev, V.G. Storchak, Emerging two-dimensional ferromagnetism in silicene materials, Nature communications 9(1) (2018) 1672-1672.
  • A.M. Al Alawi, S.W. Majoni, H. Falhammar, Magnesium and Human Health: Perspectives and Research Directions, International journal of endocrinology 2018 (2018) 9041694-9041694.
  • A.L. Tumurbaatar B, Park C, Kim CS Computational Analysis of the Design and Experimental Application of the Migration and Durability Testing Device for Oesophageal Stent, Biomaterials and Medical Applications 1(1) (2017) 8.
  • A.A. Demircali, H. Uvet, Stabilization of Microrobot Motion Characteristics in Liquid Media, Micromachines 9(7) (2018) 363.
  • A. Voulodimos, N. Doulamis, A. Doulamis, E. Protopapadakis, Deep Learning for Computer Vision: A Brief Review, Computational intelligence and neuroscience 2018 (2018) 7068349-7068349.
  • A. Tahmassebi, A.H. Gandomi, S. Fong, A. Meyer-Baese, S.Y. Foo, Multi-stage optimization of a deep model: A case study on ground motion modeling, PloS one 13(9) (2018) e0203829-e0203829.
  • A. Ramachandra Kurup Sasikala, A.R. Unnithan, R.G. Thomas, T. Batgerel, Y.Y. Jeong, C.H. Park, C.S. Kim, Hexa-functional tumour-seeking nano voyagers and annihilators for synergistic cancer theranostic applications, Nanoscale 10(41) (2018) 19568-19578.
  • A. Malekzadeh, A. Heydarinasab, M. Jahangiri, Magnetic field effect on laminar heat transfer in a pipe for thermal entry region, Journal of Mechanical Science and Technology 25(4) (2011) 877-884.
  • A. K lsch, M.Z. Afzal, M. Ebbecke, M. Liwicki, Real-Time Document Image Classification using Deep CNN and Extreme Learning Machines, CoRR abs/1711.05862 (2017).
  • A. Janowczyk, A. Madabhushi, Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases, Journal of Pathology Informatics 7(1) (2016) 29-29.
  • A. Iwanaga, A. Egashira, K. Minami, H. Saeki, M. Yamamoto, M. Morita, T. Seto, M. Takenoyama, M. Ueda, K. Okushima, M. Shimokawa, Y. Toh, T. Okamura, Evaluation of esophageal and airway stent placement for patients with advanced and recurrent esophageal cancer, Esophagus 13(3) (2016) 283-289.
  • A deep learning-based multi-model ensemble method for cancer prediction, Computer Methods and Programs in Biomedicine 153 (2018) 1 - 9.