Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Yu, Myeong Sang
2020.
Application of Machine Learning in Rhinology: A State of the Art Review.
Korean Journal of Otorhinolaryngology-Head and Neck Surgery,
Vol. 63,
Issue. 8,
p.
341.
Chawdhary, Gaurav
and
Shoman, Nael
2021.
Emerging artificial intelligence applications in otological imaging.
Current Opinion in Otolaryngology & Head & Neck Surgery,
Vol. 29,
Issue. 5,
p.
357.
Byun, Hayoung
Yu, Sangjoon
Oh, Jaehoon
Bae, Junwon
Yoon, Myeong Seong
Lee, Seung Hwan
Chung, Jae Ho
and
Kim, Tae Hyun
2021.
An Assistive Role of a Machine Learning Network in Diagnosis of Middle Ear Diseases.
Journal of Clinical Medicine,
Vol. 10,
Issue. 15,
p.
3198.
García-Domínguez, Antonio
Galván-Tejada, Carlos E.
Brena, Ramón F.
Aguileta, Antonio A.
Galván-Tejada, Jorge I.
Gamboa-Rosales, Hamurabi
Celaya-Padilla, José M.
and
Luna-García, Huizilopoztli
2021.
Children’s Activity Classification for Domestic Risk Scenarios Using Environmental Sound and a Bayesian Network.
Healthcare,
Vol. 9,
Issue. 7,
p.
884.
Kashani, Rustin G.
Młyńczak, Marcel C.
Zarabanda, David
Solis-Pazmino, Paola
Huland, David M.
Ahmad, Iram N.
Singh, Surya P.
and
Valdez, Tulio A.
2021.
Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach.
Scientific Reports,
Vol. 11,
Issue. 1,
Mothershaw, Adam
Smith, Anthony C.
Perry, Christopher F.
Brown, Cecil
and
Caffery, Liam J.
2021.
Does artificial intelligence have a role in telehealth screening of ear disease in Indigenous children in Australia?.
Australian Journal of Otolaryngology,
Vol. 4,
Issue. ,
p.
0.
Wang, Zheng
Song, Jian
Su, Ri
Hou, Muzhou
Qi, Min
Zhang, Jianglin
and
Wu, Xuewen
2022.
Structure-aware deep learning for chronic middle ear disease.
Expert Systems with Applications,
Vol. 194,
Issue. ,
p.
116519.
Habib, Al-Rahim
Crossland, Graeme
Patel, Hemi
Wong, Eugene
Kong, Kelvin
Gunasekera, Hasantha
Richards, Brent
Caffery, Liam
Perry, Chris
Sacks, Raymond
Kumar, Ashnil
and
Singh, Narinder
2022.
An Artificial Intelligence Computer-vision Algorithm to Triage Otoscopic Images From Australian Aboriginal and Torres Strait Islander Children.
Otology & Neurotology,
Vol. 43,
Issue. 4,
p.
481.
Canares, Therese L
Wang, Weiyao
Unberath, Mathias
and
Clark, James H
2022.
Artificial intelligence to diagnose ear disease using otoscopic image analysis: a review.
Journal of Investigative Medicine,
Vol. 70,
Issue. 2,
p.
354.
Wu, Qingwu
Wang, Xinyue
Liang, Guixian
Luo, Xin
Zhou, Min
Deng, Huiyi
Zhang, Yana
Huang, Xuekun
and
Yang, Qintai
2023.
Advances in Image‐Based Artificial Intelligence in Otorhinolaryngology–Head and Neck Surgery: A Systematic Review.
Otolaryngology–Head and Neck Surgery,
Vol. 169,
Issue. 5,
p.
1132.
Ding, Xin
Huang, Yu
Tian, Xu
Zhao, Yang
Feng, Guodong
and
Gao, Zhiqiang
2023.
Diagnosis, Treatment, and Management of Otitis Media with Artificial Intelligence.
Diagnostics,
Vol. 13,
Issue. 13,
p.
2309.
Tsilivigkos, Christos
Athanasopoulos, Michail
Micco, Riccardo di
Giotakis, Aris
Mastronikolis, Nicholas S.
Mulita, Francesk
Verras, Georgios-Ioannis
Maroulis, Ioannis
and
Giotakis, Evangelos
2023.
Deep Learning Techniques and Imaging in Otorhinolaryngology—A State-of-the-Art Review.
Journal of Clinical Medicine,
Vol. 12,
Issue. 22,
p.
6973.
Taylor, Alon
Habib, Al‐Rahim
Kumar, Ashnil
Wong, Eugene
Hasan, Zubair
and
Singh, Narinder
2023.
An artificial intelligence algorithm for the classification of sphenoid sinus pneumatisation on sinus computed tomography scans.
Clinical Otolaryngology,
Vol. 48,
Issue. 6,
p.
888.
Ngombu, Stephany
Binol, Hamidullah
Gurcan, Metin N.
and
Moberly, Aaron C.
2023.
Advances in Artificial Intelligence to Diagnose Otitis Media: State of the Art Review.
Otolaryngology–Head and Neck Surgery,
Vol. 168,
Issue. 4,
p.
635.
Song, Dahye
Kim, Taewan
Lee, Yeonjoon
and
Kim, Jaeyoung
2023.
Image-Based Artificial Intelligence Technology for Diagnosing Middle Ear Diseases: A Systematic Review.
Journal of Clinical Medicine,
Vol. 12,
Issue. 18,
p.
5831.
Shim, Jae-Hyuk
Sunwoo, Woongsang
Choi, Byung Yoon
Kim, Kwang Gi
and
Kim, Young Jae
2023.
Improving the Accuracy of Otitis Media with Effusion Diagnosis in Pediatric Patients Using Deep Learning.
Bioengineering,
Vol. 10,
Issue. 11,
p.
1337.
Habib, Al-Rahim
Xu, Yixi
Bock, Kris
Mohanty, Shrestha
Sederholm, Tina
Weeks, William B.
Dodhia, Rahul
Ferres, Juan Lavista
Perry, Chris
Sacks, Raymond
and
Singh, Narinder
2023.
Evaluating the generalizability of deep learning image classification algorithms to detect middle ear disease using otoscopy.
Scientific Reports,
Vol. 13,
Issue. 1,
Cao, Zuwei
Chen, Feifan
Grais, Emad M.
Yue, Fengjuan
Cai, Yuexin
Swanepoel, De Wet
and
Zhao, Fei
2023.
Machine Learning in Diagnosing Middle Ear Disorders Using Tympanic Membrane Images: A Meta‐Analysis.
The Laryngoscope,
Vol. 133,
Issue. 4,
p.
732.
Cao, Cong
Song, Jian
Su, Ri
Wu, Xuewen
Wang, Zheng
and
Hou, Muzhou
2023.
Structure-constrained deep feature fusion for chronic otitis media and cholesteatoma identification.
Multimedia Tools and Applications,
Vol. 82,
Issue. 29,
p.
45869.
Tseng, Christopher C.
Lim, Valerie
and
Jyung, Robert W.
2023.
Use of artificial intelligence for the diagnosis of cholesteatoma.
Laryngoscope Investigative Otolaryngology,
Vol. 8,
Issue. 1,
p.
201.