Understanding Standard Procedure in Auditory Brainstem Response: Importance of Normative Data.

The auditory brainstem response (ABR) is a noninvasive test that measures neural activity in response to auditory stimuli. Racial differences in head shape have provided strong evidence for specific normative data and accurate device calibration. International standards emphasize the need for standardized procedures and references.

Improving Accuracy and Reliability of Hearing Tests: Measurement Standards for Audiometric Devices.

Pure-tone audiometry, using an audiometer, is the fundamental hearing test for diagnosing hearing loss. The requirements of the devices and the detailed process for calibrating the related equipment are described in international standards. However, traceable calibration and uncertainty evaluation processes are not widely accepted or applied to the qualification and maintenance of audiometric equipment.

Human-machine cooperation meta-model for clinical diagnosis by adaptation to human expert's diagnostic characteristics.

Artificial intelligence (AI) using deep learning approaches the capabilities of human experts in medical image diagnosis. However, due to liability issues in medical decisions, AI is often relegated to an assistant role. Based on this responsibility constraint, the effective use of AI to assist human intelligence in real-world clinics remains a challenge.

Differential Biases and Variabilities of Deep Learning-Based Artificial Intelligence and Human Experts in Clinical Diagnosis: Retrospective Cohort and Survey Study.

Background: Deep learning (DL)-based artificial intelligence may have different diagnostic characteristics than human experts in medical diagnosis. As a data-driven knowledge system, heterogeneous population incidence in the clinical world is considered to cause more bias to DL than clinicians. Conversely, by experiencing limited numbers of cases, human experts may exhibit large interindividual variability.

Local Differential Privacy in the Medical Domain to Protect Sensitive Information: Algorithm Development and Real-World Validation.

Background: Privacy is of increasing interest in the present big data era, particularly the privacy of medical data. Specifically, differential privacy has emerged as the standard method for preservation of privacy during data analysis and publishing.

Objective: Using machine learning techniques, we applied differential privacy to medical data with diverse parameters and checked the feasibility of our algorithms with synthetic data as well as the balance between data privacy and utility.

Implementing Vertical Federated Learning Using Autoencoders: Practical Application, Generalizability, and Utility Study.

Background: Machine learning (ML) is now widely deployed in our everyday lives. Building robust ML models requires a massive amount of data for training. Traditional ML algorithms require training data centralization, which raises privacy and data governance issues.

Feasibility of Asynchronous and Automated Telemedicine in Otolaryngology: Prospective Cross-Sectional Study.

Background: COVID-19 often causes respiratory symptoms, making otolaryngology offices one of the most susceptible places for community transmission of the virus. Thus, telemedicine may benefit both patients and physicians.

Objective: This study aims to explore the feasibility of telemedicine for the diagnosis of all otologic disease types.

Machine learning approach for prediction of hearing preservation in vestibular schwannoma surgery.

In vestibular schwannoma patients with functional hearing status, surgical resection while preserving the hearing is feasible. Hearing levels, tumor size, and location of the tumor have been known to be candidates of predictors. We used a machine learning approach to predict hearing outcomes in vestibular schwannoma patients who underwent hearing preservation surgery: middle cranial fossa, or retrosigmoid approach.

Automated diagnosis of ear disease using ensemble deep learning with a big otoendoscopy image database.

Background: Ear and mastoid disease can easily be treated by early detection and appropriate medical care. However, short of specialists and relatively low diagnostic accuracy calls for a new way of diagnostic strategy, in which deep learning may play a significant role. The current study presents a machine learning model to automatically diagnose ear disease using a large database of otoendoscopic images acquired in the clinical environment.

The Feasibility of a Modified Exclusive Endoscopic Transcanal Transpromontorial Approach for Vestibular Schwannomas.

 We evaluated the feasibility of an exclusive endoscopic transcanal transpromontorial approach (EETTA) for the treatment of small vestibular schwannomas (VSs) limited to the internal auditory canal (IAC), and introduced a modification without external auditory canal closure.  Between June 2016 and June 2017, seven patients with VS underwent surgery using a modified EETTA. Treatment outcomes, including efficacy of tumor resection, preservation of function, operation time, and quality of life (QOL), were evaluated.

Transoral Robotic Surgery With Transoral Retropharyngeal Lymph Node Dissection in Patients With Tonsillar Cancer: Anatomical Points, Surgical Techniques, and Clinical Usefulness.

Objective: The purpose of this study was to evaluate the clinical usefulness of TORS and transoral robotic retropharyngeal lymph node (RPLN) dissection in tonsillar cancer patients with suspicious RPLN metastasis.

Methods: From April 2008 to March 2014, 71 patients with tonsillar cancer underwent transoral robotic surgery and standard neck dissection at the Yonsei Head and Neck Cancer Center.

Results: Three patients underwent transoral robotic ropharyngectomy with transoral robotic RPLN dissection because of suspicious RPLN metastasis.

A New Clinical Trial of Neoadjuvant Chemotherapy Combined With Transoral Robotic Surgery and Customized Adjuvant Therapy for Patients With T3 or T4 Oropharyngeal Cancer.

Background: A prospective clinical trial of combination neoadjuvant chemotherapy, transoral robotic surgery (TORS), and customized adjuvant therapy for patients with locally advanced oropharyngeal cancer was conducted.

Methods: Between July 2009 and October 2016, 31 patients were enrolled in this clinical trial.

Results: The primary lesions were located in the tonsils of 27 patients and in the base of the tongue of 4 patients.

The long-term oncological and functional outcomes of transoral robotic surgery in patients with hypopharyngeal cancer.

Objective: We conducted a prospective clinical trial of transoral robotic surgery in patients with hypopharyngeal cancer and herein report the long-term oncological and functional outcomes.

Materials And Methods: Between April 2008 and March 2014, 45 patients diagnosed with hypopharyngeal cancer participated in this prospective study.

Results: All patients were male with a mean age of 66.