Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery

Tama, Bayu Adhi; Kim, Do Hyun; Kim, Gyuwon; Kim, Soo Whan; Lee, Seung−Chul

doi:10.21053/ceo.2020.00654

Cited by 38 publications

(30 citation statements)

References 123 publications

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“…Distinct from the articles [32] and guidelines [33] published during the first months of the pandemic, this review presenting the "COVID-19 organization protocol" of the research hospital "Casa Sollievo della Sofferenza" offers a different and enduring perspective accompanied by a new awareness of the disease and a gradual return to elective procedures. The COVID-19 pandemic has undoubtedly only accelerated the process toward the health care system of the future, where telemedicine [34], artificial intelligence [35] and mobile applications [36] are going to have more and more use.…”

Section: Discussionmentioning

confidence: 99%

Managing head and neck cancer patients during the COVID-19 pandemic: the experience of a tertiary referral center in southern Italy

Longo

Trecca

D’Ecclesia

et al. 2021

Infect Agents Cancer

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Background The medical community has been deeply involved in fighting the Coronavirus disease 2019 (COVID-19) pandemic and, as a consequence, the care of non-COVID-19 patients has been impacted. However, the treatment of head and neck cancer patients is not deferrable, and an integrated strategy is required. The aim of the current article is to present the experience in the management of head and neck patients during the COVID-19 pandemic at the research hospital “Casa Sollievo della Sofferenza”. This review contains replicable and widely usable instructions on how to avoid delays in the diagnosis and treatment of head and neck tumors and to ensure a gradual return to elective procedures. Main text The Head and Neck Department of the research hospital “Casa Sollievo della Sofferenza” includes an Otolaryngology and a Maxillofacial Surgery Unit, both of which deal with the diagnosis and treatment of benign and malignant pathologies of the head and neck, as well as urgent/emergent consultations and surgical procedures that necessitate time sensitive operative management, such as cochlear implantation (CI). Given these premises and the complexity of the Department, the “COVID-19 organizing protocol” of the research hospital “Casa Sollievo della Sofferenza” was divided into two phases in accordance with the different stages of the pandemic and the priority of treatment. Special attention was given to the medical surveillance of health care workers and hospitalized patients, to the organization of the outpatient clinic and the operating setting as well as to the implementation of telehealth systems. Conclusions The COVID-19 pandemic is going to be a long-term situation with lasting effects on the public health and the entire society. Therefore, an efficient health care system has to adopt a double strategy: always being ready for a “new wave” of the pandemic and not forgetting non-COVID-19 patients, among whom head and neck cancer patients represent a priority. More than 1 year since the first outbreak in Wuhan, this review offers a unique and helpful perspective that incorporates awareness of the disease.

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Section: Discussionmentioning

confidence: 99%

Managing head and neck cancer patients during the COVID-19 pandemic: the experience of a tertiary referral center in southern Italy

Longo

Trecca

D’Ecclesia

et al. 2021

Infect Agents Cancer

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“…The contrast variance in MRI images and number of slices recorded while capturing is not sufficient and it is quite hard to recognize the patterns in dysplasia tumour grades. In [8] Bayu et al, reviewed the importance and contributions of machine learning in medial field and mainly in tumour recognition and classification. Around 460 articles were reviewed and discussed elaborately about the machine learning and deep learning influence on medical imaging for detection and classification.…”

Section: Literature Reviewmentioning

confidence: 99%

Severity Grade Recognition for Nasal Cavity Tumours Using D閏or CNN

Mathialagan¹,

Malathy²

2022

Intelligent Automation &Amp; Soft Computing

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Nasal cavity and paranasal sinus tumours that occur in the respiratory tract are the most life-threatening disease in the world. The human respiratory tract has many sites which has different mucosal lining like frontal, parred, sphenoid and ethmoid sinuses. Nasal cavity tumours can occur at any different mucosal linings and chances of prognosis possibility from one nasal cavity site to another site is very high. The paranasal sinus tumours can metastases to oral cavity and digestive tracts may lead to excessive survival complications. Grading the respiratory tract tumours with dysplasia cases are more challenging using manual pathological procedures. Manual microscopic biopsy tissue analysis is time consuming and chances of occurring interobserver variability problems are very high. To avoid nasal cavity tumour grade misclassification a State-Of-The-Art Automated Décor CNN model is proposed. The automated nasal cavity tumour grading classification model is designed to troubleshoot the stain artifact present in the biopsy tissue samples. Major nasal cavity sites are analysed to find the abnormal epithelium. The automated morphological characteristic findings with décor CNN model in biopsy images are promising. The model achieves the classification accuracy of 98% with less training, testing and validation errors compared to other transfer learning convolution neural network models.

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“…Im Bereich künstliche Intelligenz und maschinelles Lernen gibt es auch im HNO-Fachgebiet Anstrengungen und Aktivitäten. Eine Übersichtsarbeit zum Thema identifizierte 90 Studien, die den Einsatz künstlicher Intelligenz insbesondere in den Bereichen Bildanalyse, Sprachanalyse, Gen-Analyse sowie Elektroencephalogramm, Elektrokardiogramm und Apnoe-Hypopnoe-Index anhand klinischer Daten untersuchten und berichtete erste Erfolge, postulierte aber auch weiteren Forschungsbedarf [ 43 ]. Digitalisierung, künstliche Intelligenz und Big Data werden als Konzept angepriesen, mit dem wir an der Schwelle zu einer Präzisionsmedizin stehen, die in Kürze fehlerfrei diagnostiziert und therapiert.…”

Section: „Wo Gehen Wir Hin?“unclassified

Wo kommen wir her? Wo stehen wir? Wo gehen wir hin?

Plontke

2022

HNO

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Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery

Cited by 38 publications

References 123 publications

Managing head and neck cancer patients during the COVID-19 pandemic: the experience of a tertiary referral center in southern Italy

Managing head and neck cancer patients during the COVID-19 pandemic: the experience of a tertiary referral center in southern Italy

Severity Grade Recognition for Nasal Cavity Tumours Using D閏or CNN

Wo kommen wir her? Wo stehen wir? Wo gehen wir hin?

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