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Cited by in F6Publishing
For: Livingstone D, Talai AS, Chau J, Forkert ND. Building an Otoscopic screening prototype tool using deep learning. J Otolaryngol Head Neck Surg 2019;48:66. [PMID: 31771647 DOI: 10.1186/s40463-019-0389-9] [Cited by in Crossref: 12] [Cited by in F6Publishing: 9] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
1 Lo Vercio L, Amador K, Bannister JJ, Crites S, Gutierrez A, MacDonald ME, Moore J, Mouches P, Rajasheka D, Schimert S, Subbanna N, Tuladhar A, Wang N, Wilms M, Winder A, Forkert ND. Supervised machine learning tools: a tutorial for clinicians. J Neural Eng 2020. [PMID: 33036008 DOI: 10.1088/1741-2552/abbff2] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
2 Won J, Monroy GL, Dsouza RI, Spillman DR Jr, McJunkin J, Porter RG, Shi J, Aksamitiene E, Sherwood M, Stiger L, Boppart SA. Handheld Briefcase Optical Coherence Tomography with Real-Time Machine Learning Classifier for Middle Ear Infections. Biosensors (Basel) 2021;11:143. [PMID: 34063695 DOI: 10.3390/bios11050143] [Reference Citation Analysis]
3 Schuster-Bruce JR, Ali A, Van M, Rogel-Salazar J, Ofo E, Shamil E. A randomised trial to assess the educational benefit of a smartphone otoscope in undergraduate medical training. Eur Arch Otorhinolaryngol 2021;278:1799-804. [PMID: 32960350 DOI: 10.1007/s00405-020-06373-1] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Manco L, Maffei N, Strolin S, Vichi S, Bottazzi L, Strigari L. Basic of machine learning and deep learning in imaging for medical physicists. Physica Medica 2021;83:194-205. [DOI: 10.1016/j.ejmp.2021.03.026] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
5 Bhutta MF, Swanepoel W, Fagan J. ENT from afar: Opportunities for remote patient assessment, clinical management, teaching and learning. Clin Otolaryngol 2021;46:689-91. [PMID: 33872469 DOI: 10.1111/coa.13784] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Tsutsumi K, Goshtasbi K, Risbud A, Khosravi P, Pang JC, Lin HW, Djalilian HR, Abouzari M. A Web-Based Deep Learning Model for Automated Diagnosis of Otoscopic Images. Otol Neurotol 2021. [PMID: 34191783 DOI: 10.1097/MAO.0000000000003210] [Reference Citation Analysis]
7 Schuster-Bruce J, Shetty P, O'Donovan J, Mandavia R, Sokdavy T, Bhutta MF. Comparative performance of prediction model, non-expert and telediagnosis of common external and middle ear disease using a patient cohort from Cambodia that included one hundred and thirty-eight ears. Clin Otolaryngol 2021;46:635-41. [PMID: 33341099 DOI: 10.1111/coa.13695] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
8 Esteva A, Chou K, Yeung S, Naik N, Madani A, Mottaghi A, Liu Y, Topol E, Dean J, Socher R. Deep learning-enabled medical computer vision. NPJ Digit Med. 2021;4:5. [PMID: 33420381 DOI: 10.1038/s41746-020-00376-2] [Cited by in Crossref: 16] [Cited by in F6Publishing: 9] [Article Influence: 16.0] [Reference Citation Analysis]
9 Tama BA, Kim DH, Kim G, Kim SW, Lee S. Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery. Clin Exp Otorhinolaryngol 2020;13:326-39. [PMID: 32631041 DOI: 10.21053/ceo.2020.00654] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]