Application of Artificial Intelligence in Medicine: An Overview

International evaluation of an AI system for breast cancer screening

McKinney, S. M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., Back, T., Chesus, M., Corrado, G. S., Darzi, A., et al. (2020) · Nature · doi:10.1038/s41586-019-1799-6 · Cited by 3,287 · see citing works

Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

Coudray, N., Ocampo, P. S., Sakellaropoulos, T., Narula, N., Snuderl, M., Fenyö, D., Moreira, A. L., Razavian, N., & Tsirigos, A. (2018) · Nature Medicine · doi:10.1038/s41591-018-0177-5 · Cited by 2,930 · see citing works

Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology

Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V., & Madabhushi, A. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0252-y · Cited by 1,698 · see citing works

Artificial Intelligence (AI) applications for COVID-19 pandemic

Vaishya, R., Javaid, M., Khan, I. H., & Haleem, A. (2020) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2020.04.012 · Cited by 1,502 · see citing works

A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study

Sun, R., Limkin, E. J., Vakalopoulou, M., Dercle, L., Champiat, S., Han, S. R., Verlingue, L., Brandao, D., Lancia, A., Ammari, S., et al. (2018) · The Lancet Oncology · doi:10.1016/s1470-2045(18)30413-3 · Cited by 1,236 · cited 1× · see citing works

Internist-I, an Experimental Computer-Based Diagnostic Consultant for General Internal Medicine

Miller, R. A., Pople, H. E., & Myers, J. D. (1982) · New England Journal of Medicine · doi:10.1056/nejm198208193070803 · Cited by 1,129 · see citing works

History of artificial intelligence in medicine

Kaul, V., Enslin, S., & Gross, S. A. (2020) · Gastrointestinal Endoscopy · doi:10.1016/j.gie.2020.06.040 · Cited by 1,094 · see citing works

Prediction of acute myeloid leukaemia risk in healthy individuals

Abelson, S., Collord, G., Ng, S. W. K., Weissbrod, O., Mendelson Cohen, N., Niemeyer, E., Barda, N., Zuzarte, P. C., Heisler, L., Sundaravadanam, Y., et al. (2018) · Nature · doi:10.1038/s41586-018-0317-6 · Cited by 850 · see citing works

Introduction to artificial intelligence in medicine

Mintz, Y., & Brodie, R. (2019) · Minimally Invasive Therapy & Allied Technologies · doi:10.1080/13645706.2019.1575882 · Cited by 818 · see citing works

Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists

Rodriguez-Ruiz, A., Lång, K., Gubern-Merida, A., Broeders, M., Gennaro, G., Clauser, P., Helbich, T. H., Chevalier, M., Tan, T., Mertelmeier, T., et al. (2019) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/djy222 · Cited by 692 · see citing works

The coming of age of artificial intelligence in medicine

Patel, V. L., Shortliffe, E. H., Mario Stefanelli, A., Peter Szolovits, B., Berthold, M. R., Bellazzi, R., & Abu–Hanna, A. (2008) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2008.07.017 · Cited by 629 · see citing works

Artificial Intelligence in Anesthesiology

Hashimoto, D. A., Witkowski, E. R., Gao, L., Meireles, O. R., & Rosman, G. (2019) · Anesthesiology · doi:10.1097/aln.0000000000002960 · Cited by 545 · see citing works

Computer-based consultations in clinical therapeutics: Explanation and rule acquisition capabilities of the MYCIN system

Shortliffe, E. H., Davis, R., Axline, S. G., Buchanan, B. G., Green, C. C., & Cohen, S. N. (1975) · Computers and Biomedical Research · doi:10.1016/0010-4809(75)90009-9 · Cited by 493 · see citing works

Artificial intelligence as the next step towards precision pathology

Ács, B., Rantalainen, M., & Hartman, J. (2020) · Journal of Internal Medicine · doi:10.1111/joim.13030 · Cited by 464 · see citing works

Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumours

Iizuka, O., Kanavati, F., Kato, K., Rambeau, M., Arihiro, K., & Tsuneki, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-58467-9 · Cited by 404 · see citing works

New machine learning method for image-based diagnosis of COVID-19

Elaziz, M. A., Hosny, K. M., Salah, A., Darwish, M. M., Lu, S., & Sahlol, A. T. (2020) · PLoS ONE · doi:10.1371/journal.pone.0235187 · Cited by 400 · see citing works

Pathology image analysis using segmentation deep learning algorithms

Wang, S., Yang, D. M., Rong, R., Zhan, X., & Xiao, G. (2019) · The American Journal of Pathology · doi:10.1016/j.ajpath.2019.05.007 · Cited by 382 · see citing works

3D printing: Principles and pharmaceutical applications of selective laser sintering

Awad, A., Fina, F., Goyanes, Á., Gaisford, S., & Basit, A. W. (2020) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2020.119594 · Cited by 375 · see citing works

The Virtual Operative Assistant: An explainable artificial intelligence tool for simulation-based training in surgery and medicine

Mirchi, N., Bissonnette, V., Yilmaz, R., Ledwos, N., Winkler-Schwartz, A., & Del Maestro, R. F. (2020) · PLOS ONE · doi:10.1371/journal.pone.0229596 · Cited by 296 · see citing works

Artificial Intelligence in Lung Cancer Pathology Image Analysis

Wang, S., Yang, D. M., Rong, R., Zhan, X., Fujimoto, J., Liu, H., Minna, J. D., Wistuba, I. I., Xie, Y., & Xiao, G. (2019) · Cancers · doi:10.3390/cancers11111673 · Cited by 293 · see citing works

Translational AI and deep learning in diagnostic pathology

Serag, A., Ion-Margineanu, A., Qureshi, H., McMillan, R., Saint Martin, M.-J., Diamond, J., O'Reilly, P., & Hamilton, P. (2019) · Frontiers in Medicine · doi:10.3389/fmed.2019.00185 · Cited by 274 · see citing works

Artificial Intelligence for COVID-19 Drug Discovery and Vaccine Development

Arshadi, A. K., Webb, J., Salem, M., Cruz, E., Calad-Thomson, S., Ghadirian, N., Collins, J., Diez‐Cecilia, E., Kelly, B., Goodarzi, H., et al. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00065 · Cited by 245 · see citing works

Cranioplasty: A Comprehensive Review of the History, Materials, Surgical Aspects, and Complications

Alkhaibary, A., Alharbi, A., Alnefaie, N. T., et al. (2020) · World Neurosurgery · doi:10.1016/j.wneu.2020.04.211 · Cited by 243 · see citing works

Reconstruction of Large Skeletal Defects: Current Clinical Therapeutic Strategies and Future Directions Using 3D Printing

Vidal, L., Kampleitner, C., Brennan, M. Á., et al. (2020) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2020.00061 · Cited by 239 · see citing works

The First Clinical Application of a “Hands-On” Robotic Knee Surgery System

Jakopec, M., Harris, S., y Baena, F. R., Gomes, P., Cobb, J. P., & Davies, B. (2001) · Computer Aided Surgery · doi:10.1002/igs.10023 · Cited by 223 · see citing works

Artificial intelligence approach fighting COVID-19 with repurposing drugs

Ke, Y., Peng, T.-T., Yeh, T., Huang, W.-Z., Chang, S.-E., Wu, S.-H., Hung, H., Hsu, T., Lee, S., Song, J.-S., et al. (2020) · Biomedical Journal · doi:10.1016/j.bj.2020.05.001 · Cited by 222 · see citing works

Weakly-supervised learning for lung carcinoma classification using deep learning

Kanavati, F., Toyokawa, G., Momosaki, S., Rambeau, M., Kozuma, Y., Shoji, F., Yamazaki, K., Takeo, S., Iizuka, O., & Tsuneki, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-66333-x · Cited by 218 · see citing works

Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study

Rodríguez‐Ruiz, A., Lång, K., Gubern‐Mérida, A., Teuwen, J., Broeders, M. J. M., Gennaro, G., Clauser, P., Helbich, T. H., Chevalier, M. L., Mertelmeier, T., et al. (2019) · European Radiology · doi:10.1007/s00330-019-06186-9 · Cited by 209 · see citing works

Application of Artificial Intelligence in COVID-19 drug repurposing

Mohanty, S., Rashid, M. H. A., Mridul, M., Mohanty, C., & Swayamsiddha, S. (2020) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2020.06.068 · Cited by 207 · see citing works

Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory

Lin, Y.-W., Zhou, Y., Faghri, F., Shaw, M. J., & Campbell, R. H. (2019) · PLoS ONE · doi:10.1371/journal.pone.0218942 · Cited by 186 · see citing works

3D Printing in Medicine for Preoperative Surgical Planning: A Review

Tejo‐Otero, A., Buj-Corral, I., & Fenollosa-Artés, F. (2019) · Annals of Biomedical Engineering · doi:10.1007/s10439-019-02411-0 · Cited by 185 · see citing works

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients

Heydon, P., Egan, C. A., Bolter, L., Chambers, R., Anderson, J., Aldington, S. J., STRATTON, I. M., Scanlon, P. H., Webster, L., Mann, S. S., et al. (2020) · British Journal of Ophthalmology · doi:10.1136/bjophthalmol-2020-316594 · Cited by 183 · see citing works

Advanced Medical Use of Three-Dimensional Imaging in Congenital Heart Disease: Augmented Reality, Mixed Reality, Virtual Reality, and Three-Dimensional Printing

Goo, H. W., Park, S. J., & Yoo, S. (2020) · Korean Journal of Radiology · doi:10.3348/kjr.2019.0625 · Cited by 177 · see citing works

Optimizing Students’ Mental Health and Academic Performance: AI-Enhanced Life Crafting

Dekker, I., De Jong, E. M., Schippers, M. C., De Bruijn-Smolders, M., Alexiou, A., & Giesbers, B. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01063 · Cited by 176 · see citing works

Glaucoma consultation by computer

Weiss, S. M., Kulikowski, C. A., & Safir, A. (1978) · Computers in Biology and Medicine · doi:10.1016/0010-4825(78)90011-2 · Cited by 173 · see citing works

Application and Prospect of Mixed Reality Technology in Medical Field

Hu, H., Feng, X., Shao, Z., Xie, M., Xu, S., Wu, X., & Ye, Z. (2019) · Current Medical Science · doi:10.1007/s11596-019-1992-8 · Cited by 170 · see citing works

Artificial intelligence in chemistry and drug design

Brown, N., Ertl, P., Lewis, R., Luksch, T., Reker, D., & Schneider, N. (2020) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-020-00317-x · Cited by 165 · see citing works

The First Clinical Application of a “Hands-On” Robotic Knee Surgery System

Jakopec, M., Harris, S. J., y Baena, F. R., et al. (2001) · Computer Aided Surgery · doi:10.3109/10929080109146302 · Cited by 157 · see citing works

Glomerulosclerosis identification in whole slide images using semantic segmentation

Bueno, G., Fernández-Carrobles, M. M., Lucía, G.-L., & Déniz, Ó. (2019) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2019.105273 · Cited by 156 · see citing works

Regenerative medicine, organ bioengineering and transplantation

Edgar, L., Pu, T., Porter, B., Aziz, J., Lapointe, C., Asthana, A., & Orlando, G. (2020) · British Journal of Surgery · doi:10.1002/bjs.11686 · Cited by 153 · see citing works

The emerging roles of artificial intelligence in cancer drug development and precision therapy

Liang, G., Fan, W., Luo, H., & Zhu, X. M. (2020) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2020.110255 · Cited by 149 · see citing works

Beginnings of Artificial Intelligence in Medicine (AIM): Computational Artifice Assisting Scientific Inquiry and Clinical Art – with Reflections on Present AIM Challenges

Kulikowski, C. A. (2019) · Yearbook of Medical Informatics · doi:10.1055/s-0039-1677895 · Cited by 144 · see citing works

Machine learning approaches for pathologic diagnosis

Komura, D., & Ishikawa, S. (2019) · Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin · doi:10.1007/s00428-019-02594-w · Cited by 143 · see citing works

A review of thyroid gland segmentation and thyroid nodule segmentation methods for medical ultrasound images

Chen, J., You, H., & Li, K. (2020) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2020.105329 · Cited by 142 · see citing works

3D printing for oral drug delivery: a new tool to customize drug delivery

Pandey, M., Choudhury, H., Fern, J. L. C., Kee, A. T. K., Kou, J., Jing, J. L. J., Her, H. C., Yong, H. S., Ming, H. C., Bhattamisra, S. K., et al. (2020) · Drug Delivery and Translational Research · doi:10.1007/s13346-020-00737-0 · Cited by 135 · see citing works

A Discussion of Virtual Reality As a New Tool for Training Healthcare Professionals

Fertleman, C. R., Aubugeau-Williams, P., Sher, C., Lim, A.-N., Lumley, S., Delacroix, S., & Pan, X. (2018) · Frontiers in Public Health · doi:10.3389/fpubh.2018.00044 · Cited by 132 · see citing works

Automated detection and quantification of COVID-19 pneumonia: CT imaging analysis by a deep learning-based software

Zhang, H.-T., Zhang, H., Zhang, H.-H., Nan, Y., Zhao, Y., Fu, E.-Q., Xie, Y.-H., Liu, W., Li, W.-P., Zhang, H.-J., et al. (2020) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-020-04953-1 · Cited by 124 · see citing works

Ultrasound Image-Based Diagnosis of Malignant Thyroid Nodule Using Artificial Intelligence

Nguyen, D. T., Kang, J. K., Pham, T. D., Batchuluun, G., & Park, K. R. (2020) · Sensors · doi:10.3390/s20071822 · Cited by 119 · see citing works

Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study

Poncette, A.-S., Mosch, L. K., Spies, C., Schmieding, M. L., Schiefenhövel, F., Krampe, H., & Balzer, F. (2020) · Journal of Medical Internet Research · doi:10.2196/19091 · Cited by 115 · see citing works

Advanced bioinformatics rapidly identifies existing therapeutics for patients with coronavirus disease-2019 (COVID-19)

Kim, J., Zhang, J., Cha, Y., Kolitz, S. E., Funt, J. M., Escalante-Chong, R., Barrett, S., Kusko, R. L., Zeskind, B., & Kaufman, H. L. (2020) · Journal of Translational Medicine · doi:10.1186/s12967-020-02430-9 · Cited by 103 · see citing works

Three-dimensional bio-printing and bone tissue engineering: technical innovations and potential applications in maxillofacial reconstructive surgery

Salah, M., Tayebi, L., Moharamzadeh, K., et al. (2020) · Maxillofacial Plastic and Reconstructive Surgery · doi:10.1186/s40902-020-00263-6 · Cited by 102 · see citing works

3D Bioprinting for Vascularized Tissue-Engineered Bone Fabrication

Xing, F., Xiang, Z., Rommens, P. M., & Ritz, U. (2020) · Materials · doi:10.3390/ma13102278 · Cited by 97 · see citing works

Artificial Intelligence-Based Thyroid Nodule Classification Using Information from Spatial and Frequency Domains

Nguyen, D. T., Pham, T. D., Batchuluun, G., Yoon, H. S., & Park, K. R. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8111976 · Cited by 94 · see citing works

Artificial Intelligence and Machine Learning Applied at the Point of Care

Angehrn, Z., Haldna, L., Zandvliet, A. S., Gil Berglund, E., Zeeuw, J., Amzal, B., Cheung, S. Y. A., Polasek, T. M., Pfister, M., Kerbusch, T., et al. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.00759 · Cited by 93 · see citing works

Augmented reality-assisted training with selected Tai-Chi movements improves balance control and increases lower limb muscle strength in older adults: A prospective randomized trial

Chen, P.-J., Penn, I., Wei, S.-H., Chuang, L.-R., & Sung, W.-H. (2020) · Journal of Exercise Science & Fitness · doi:10.1016/j.jesf.2020.05.003 · Cited by 89 · see citing works

The System for Telementoring with Augmented Reality (STAR): A head-mounted display to improve surgical coaching and confidence in remote areas

Rojas-Muñoz, E., Cabrera, M. E., Lin, C., Andersen, D., Popescu, V. S., Anderson, K., Zarzaur, B. L., Mullis, B., & Wachs, J. P. (2020) · Surgery · doi:10.1016/j.surg.2019.11.008 · Cited by 78 · see citing works

3D printing in adult cardiovascular surgery and interventions: a systematic review

Wang, C., Zhang, L., Qin, T., Xi, Z., Sun, L., Wu, H., & Li, D. (2020) · Journal of Thoracic Disease · doi:10.21037/jtd-20-455 · Cited by 77 · see citing works

A primer on artificial intelligence and its application to endoscopy

Chahal, D., & Byrne, M. F. (2020) · Gastrointestinal Endoscopy · doi:10.1016/j.gie.2020.04.074 · Cited by 76 · see citing works

The application of 3D-printing technology in pelvic bone tumor surgery

Park, J. W., Kang, H. G., Kim, J. H., et al. (2020) · Journal of Orthopaedic Science · doi:10.1016/j.jos.2020.03.004 · Cited by 74 · see citing works

Recognizing basal cell carcinoma on smartphone‐captured digital histopathology images with a deep neural network

Jiang, Y., Xiong, J., Li, H. Y., Yang, X., Yu, W. T., Gao, M., Zhao, X., Ma, Y., Zhang, W., Guan, Y. F., et al. (2019) · British Journal of Dermatology · doi:10.1111/bjd.18026 · Cited by 72 · see citing works

Deep learning facilitates the diagnosis of adult asthma

Tomita, K., Nagao, R., Touge, H., et al. (2019) · Allergology International · doi:10.1016/j.alit.2019.04.010 · Cited by 72 · see citing works

The combination of artificial intelligence and systems biology for intelligent vaccine design

Russo, G., Reche, P. A., Pennisi, M. A., & Pappalardo, F. (2020) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2020.1791076 · Cited by 71 · see citing works

Classification of melanocytic lesions in selected and whole-slide images via convolutional neural networks

Hart, S. N., Flotte, W., Norgan, A. F., Shah, K. K., Buchan, Z. R., Mounajjed, T., & Flotte, T. J. (2019) · Journal of Pathology Informatics · doi:10.4103/jpi.jpi_32_18 · Cited by 69 · see citing works

Deep-Hipo: Multi-scale receptive field deep learning for histopathological image analysis

Kosaraju, S., Hao, J., Koh, H. M., & Kang, M. (2020) · Methods · doi:10.1016/j.ymeth.2020.05.012 · Cited by 66 · see citing works

Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation

Cannière, H. D., Corradi, F., Smeets, C. J. P. P., Schoutteten, M., Varon, C., Hoof, C. A. V., Huffel, S. V., Groenendaal, W., & Vandervoort, P. M. (2020) · Sensors · doi:10.3390/s20123601 · Cited by 66 · see citing works

An expert-led and artificial intelligence system-assisted tutoring course to improve the confidence of Chinese medical interns in suturing and ligature skills: a prospective pilot study

Yang, Y.-Y., & Shulruf, B. (2019) · Journal of Educational Evaluation for Health Professions · doi:10.3352/jeehp.2019.16.7 · Cited by 65 · see citing works

Three-dimensional Printing Technology in Orthopaedics

Skelley, N. W. M., Smith, M. J., Ma, R., et al. (2019) · Journal of the American Academy of Orthopaedic Surgeons · doi:10.5435/jaaos-d-18-00746 · Cited by 65 · see citing works

Artificial Intelligence in Drug Discovery: Into the Great Wide Open

Bajorath, J., Kearnes, S. M., Walters, W. P., et al. (2020) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.0c01077 · Cited by 65 · see citing works

Artificial Neural Networks to Assess Virtual Reality Anterior Cervical Discectomy Performance

Mirchi, N., Bissonnette, V., Ledwos, N., Winkler-Schwartz, A., Yilmaz, R., Karlık, B., & Maestro, R. F. D. (2019) · Operative Neurosurgery · doi:10.1093/ons/opz359 · Cited by 61 · see citing works

Augmented Reality–Based Rehabilitation of Gait Impairments: Case Report

Held, J. P. O., Yu, K. K., Pyles, C. O., Veerbeek, J. M., Bork, F., Heining, S.-M., Navab, N., & Luft, A. R. (2020) · JMIR mhealth and uhealth · doi:10.2196/17804 · Cited by 59 · see citing works

Advances in Tissue Engineering and Innovative Fabrication Techniques for 3-D-Structures: Translational Applications in Neurodegenerative Diseases

Rey, F., Barzaghini, B., Nardini, A., Bordoni, M., Zuccotti, G., Cereda, C., Raimondi, M. T., & Carelli, S. (2020) · Cells · doi:10.3390/cells9071636 · Cited by 59 · see citing works

Extracellular Matrix-Derived Hydrogels as Biomaterial for Different Skeletal Muscle Tissue Replacements

Boso, D., Maghin, E., Carraro, E., Giagante, M., Pavan, P. G., & Piccoli, M. (2020) · Materials · doi:10.3390/ma13112483 · Cited by 57 · see citing works

Computer-aided diagnosis of endobronchial ultrasound images using convolutional neural network

Chen, C., Lee, Y., Huang, Y., Lan, W.-R., Chang, R., Tu, C., Chen, C., & Liao, W.-C. (2019) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2019.05.020 · Cited by 56 · see citing works

Improved classification and localization approach to small bowel capsule endoscopy using convolutional neural network

Hwang, Y., Lee, H. H., Park, C., Tama, B. A., Kim, J. S., Cheung, D. Y., Chung, W. C., Cho, Y., Lee, K. M., Choi, M., et al. (2020) · Digestive Endoscopy · doi:10.1111/den.13787 · Cited by 54 · see citing works

Current applications of artificial intelligence for intraoperative decision support in surgery

Navarrete-Welton, A., & Hashimoto, D. A. (2020) · Frontiers of Medicine · doi:10.1007/s11684-020-0784-7 · Cited by 53 · see citing works

Deep learning enables automatic quantitative assessment of puborectalis muscle and urogenital hiatus in plane of minimal hiatal dimensions

van den Noort, F., van der Vaart, C. H., Grob, A. T. M., van de Waarsenburg, M. K., Slump, C. H., & van Stralen, M. (2019) · Ultrasound in Obstetrics & Gynecology · doi:10.1002/uog.20181 · Cited by 52 · cited 1× · see citing works

Molecular and phenotypic spectrum of Noonan syndrome in Chinese patients

Li, X., Yao, R., Tan, X., et al. (2019) · Clinical Genetics · doi:10.1111/cge.13588 · Cited by 51 · see citing works

Artificial intelligence-tutoring problem-based learning in ophthalmology clerkship

Wu, D., Xiang, Y., Wu, X., Yu, T., Huang, X., Zou, Y., Liu, Z., & Lin, H. (2020) · Annals of Translational Medicine · doi:10.21037/atm.2019.12.15 · Cited by 51 · see citing works

Early Feasibility Studies of Augmented Reality Navigation for Lateral Skull Base Surgery

Creighton, F. X., Unberath, M., Song, T., et al. (2020) · Otology & Neurotology · doi:10.1097/mao.0000000000002724 · Cited by 51 · see citing works

Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules

Gong, J., Liu, J.-Y., Sun, X.-W., et al. (2018) · Physics in Medicine and Biology · doi:10.1088/1361-6560/aaa610 · Cited by 49 · see citing works

Breast Ultrasound Image Synthesis using Deep Convolutional Generative Adversarial Networks

Fujioka, T., Mori, M., Kubota, K., Kikuchi, Y. S., Katsuta, L., Adachi, M., Oda, G., Nakagawa, T., Kitazume, Y., & Tateishi, U. (2019) · Diagnostics · doi:10.3390/diagnostics9040176 · Cited by 49 · see citing works

Recent advances in the technology of anesthesia

Seger, C. D., & Cannesson, M. P. (2020) · F1000Research · doi:10.12688/f1000research.24059.1 · Cited by 49 · see citing works

Utilizing artificial intelligence in endoscopy: a clinician’s guide

Namikawa, K., Hirasawa, T., Yoshio, T., Fujisaki, J., Ozawa, T., Ishihara, S., Aoki, T., Yamada, A., Koike, K., Suzuki, H., et al. (2020) · Expert Review of Gastroenterology & Hepatology · doi:10.1080/17474124.2020.1779058 · Cited by 48 · see citing works

Evaluation of a deep learning‐based computer‐aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images

Sun, C., Zhang, Y., Chang, Q., et al. (2020) · Medical Physics · doi:10.1002/mp.14301 · Cited by 47 · see citing works

A Clinical Application Study of Mixed Reality Technology Assisted Lumbar Pedicle Screws Implantation

Gu, Y., Yao, Q., Xu, Y., et al. (2020) · Medical Science Monitor · doi:10.12659/msm.924982 · Cited by 47 · see citing works

Exploiting upper-limb functional principal components for human-like motion generation of anthropomorphic robots

Averta, G., Santina, C. D., Valenza, G., Bicchi, A., & Bianchi, M. (2020) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-020-00680-8 · Cited by 46 · see citing works

Preliminary results using patient-specific 3d printed models to improve preoperative planning for correction of post-traumatic tibial deformities with circular frames

Corona, P. S., Vicente, M., Tetsworth, K. D., et al. (2018) · Injury · doi:10.1016/j.injury.2018.07.017 · Cited by 45 · see citing works

Emergency Department Capacity Planning: A Recurrent Neural Network and Simulation Approach

Nas, S., & Koyuncu, M. (2019) · Computational and Mathematical Methods in Medicine · doi:10.1155/2019/4359719 · Cited by 44 · see citing works

Urogynecological surgical mesh implants: New trends in materials, manufacturing and therapeutic approaches

Farmer, Z.-L., Domínguez‐Robles, J., Mancinelli, C., Larrañeta, E., & Lamprou, D. A. (2020) · International Journal of Pharmaceutics · doi:10.1016/j.ijpharm.2020.119512 · Cited by 44 · see citing works

Robotic thyroid surgery

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Regulating Artificial Intelligence for a Successful Pathology Future

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