Artificial intelligence in studying and evaluation of otitis media by acoustic reflectometry

Abstract. Objective: Acute otitis media (AOM) is usually associated with upper respiratory tract infections and common colds, but many times it can last longer than the initial symptoms. An acoustic reflectometry device can be used to objectify the diagnostic process. The purpose of the study was to train the neural network to identify ears with symptoms of AOM using the acoustic response of the device. Methods: An acoustic reflectometry sample of 53 ears from 39 patients was collected during laryngoscopy operation from patients with recurrent ear infections. In addition to the acoustic samples, the doctor determined whether ear had visual signs of otitis media (OM) and whether there was effusion in it. These three parameters were used in the construction of feedforward neural network. Two neural network layouts were selected, one with samples of effusion-only sick ears and the other with sick ears based on other visual indications of OM, independent of effusion. Results: The sensitivity and specificity of the trained networks were about 90%. Two different groupings of samples clearly showed that diseased ears without effusion could be identified as sick with sensitivity of 80–90%, when similar ears were included in the category of sick ears. Network with sick ears with effusion as training material had a sensitivity of 20–30% identifying sick ears without effusion. The inclusion of both types of sick ears in single network caused slight drop in sensitivity and specificity compared to just one type. Conclusion: Acoustic reflectometry can detect more than just standard cases of acute otitis media, in which effusion typically occurs. An accurate neural network for identifying sick ears without effusion can be achieved with a relatively small sample size. This indicates a possibility of conducting an in-depth analysis of other diseases within the OM group or the transition between these diseases.Tekoäly otitis median tutkimisessa ja arvioimisessa akustisella reflektometrialla. Tiivistelmä. Työtarkoitus: Akuutti otitis media (AOM) yhdistetään yleensä ylempien hengitysteiden tulehduksiin ja nuhaan, mutta monesti otitis media (OM) oireet voivat kestää tulehdustilaa tai nuhaa pidempään. Akustista reflektometriaa käyttävän laitteen avulla diagnosointi prosessia voidaan tarkastella objektiivisesti. Työn tarkoitus oli opettaa neuroverkko, mikä tunnistaa AOM-oireisen korvan akustisen reflektometrin akustisesta mittauksesta. Menetelmät: Laryngoskopiaoperaation aikana kerättiin akustisella reflektometrialla otos 53 korvasta. Operaatio suoritettiin 39 potilaalle, joilla oli uusiutuvia korvatulehduksia. Akustisten näytteiden lisäksi operaation aikana lääkäri määritti visuaaliset OM-merkit ja eritteen määrän. Näitä kolmea tietoa käytettiin eteenpäin kytkeytyvän neuroverkon rakentamiseen. Kaksi neuroverkkoa rakennettiin, joissa ensimmäisessä oli pelkästään eritettä sisältävät korvat, ja toisessa kaikki visuaalisesti OM-merkit täyttävät korvat, mukaan lukien eritettä sisältävät korvat. Tulokset: Opetettujen neuroverkkojen sensitiivisyys ja spesifisyys olivat 90 % luokkaa. Kahteen ryhmään jaettu aineisto osoitti, että sairaat eritteettömät korvat voidaan tunnistaa sairaiksi 80–90 % sensitiivisyydellä, kun neuroverkolle opetetaan sekä eritteiset että eritteettömät sairaat korvat. Pelkästään eritteisiä korvia sisältävä neuroverkko tunnisti eritteettömät sairaat korvat 20–30 % sensitiivisyydellä. Eritteisten ja eritteettömien korvien käyttö samassa neuroverkossa laski sensitiivisyyttä ja spesifisyyttä verrattuna pelkkien eritteisten käyttöön. Johtopäätökset: Akustinen reflektometria voi tunnistaa muitakin tiloja kuin tyypillisen eritteisen akuutin otitis median. Pienellä näytemäärällä voidaan saavuttaa tarkka neuroverkko, mikä tunnistaa otitis median ilman eritteen läsnäoloa. Tämä viittaa mahdollisuuteen, että syvällisellä analyysillä voidaan saada lisää tietoa taudin etenemisestä tai taudin muista tiloista

Ultrafast and Ultralight Network-Based Intelligent System for Real-time Diagnosis of Ear diseases in Any Devices

Traditional ear disease diagnosis heavily depends on experienced specialists and specialized equipment, frequently resulting in misdiagnoses, treatment delays, and financial burdens for some patients. Utilizing deep learning models for efficient ear disease diagnosis has proven effective and affordable. However, existing research overlooked model inference speed and parameter size required for deployment. To tackle these challenges, we constructed a large-scale dataset comprising eight ear disease categories and normal ear canal samples from two hospitals. Inspired by ShuffleNetV2, we developed Best-EarNet, an ultrafast and ultralight network enabling real-time ear disease diagnosis. Best-EarNet incorporates the novel Local-Global Spatial Feature Fusion Module which can capture global and local spatial information simultaneously and guide the network to focus on crucial regions within feature maps at various levels, mitigating low accuracy issues. Moreover, our network uses multiple auxiliary classification heads for efficient parameter optimization. With 0.77M parameters, Best-EarNet achieves an average frames per second of 80 on CPU. Employing transfer learning and five-fold cross-validation with 22,581 images from Hospital-1, the model achieves an impressive 95.23% accuracy. External testing on 1,652 images from Hospital-2 validates its performance, yielding 92.14% accuracy. Compared to state-of-the-art networks, Best-EarNet establishes a new state-of-the-art (SOTA) in practical applications. Most importantly, we developed an intelligent diagnosis system called Ear Keeper, which can be deployed on common electronic devices. By manipulating a compact electronic otoscope, users can perform comprehensive scanning and diagnosis of the ear canal using real-time video. This study provides a novel paradigm for ear endoscopy and other medical endoscopic image recognition applications.Comment: This manuscript has been submitted to Neural Network

Behavioral and electrophysiological assessment of children with a specific temporal processing disorder

Auditory processing disorders (APDs) have received considerable attention over the past few decades. Much of the attention has focused on the controversy surrounding the operational definition of APD, the heterogeneous nature of APD, and an appropriate test battery for APD assessment. Temporal processing deficits are one characteristic of APD and are the focus of the present investigation. This investigation reports behavioral and early electrophysiological measures in a group of children with specific temporal processing difficulties and an age-matched control group. In an effort to better describe the subjects, two language tests and the SCAN-C were administered. Significant differences were found in the language tests, SCAN-C, and behavioral tests of temporal processing. No significant differences in ABR waveform latency were found between the control and experimental group. Significant amplitude differences were found, albeit small. Binaural interaction was present in both groups. Based on the results of the present well-controlled investigation of children with temporal processing disorders, there is no indication that the auditory brainstem response recording to click stimuli is efficient in providing additional diagnosis of APD

ENT care of children and adolescents in the Brazilian public healthy system in three different municipalities

The data base of ENT care in the Brazilian public health system (Sistema Unico de Saude - SUS) will help organize public health programs. AIM: The following items were investigated in patients aged up to 17 years attended in public health system outpatient units in the city of Mariana, in the ENT screening unit, UNIFESP-EPM, and in CISMISEL: 1) The main otorhinolaryngological diagnoses; 2) The most frequently required exams, drugs, and surgical procedures and their indications; 3) The jobs of parents; the number of siblings; and 4) A statistical analysis and comparison of data in each location. MATERIAL AND METHODS: We undertook a prospective study and a statistical analysis of variables that were gathered during the first visit. RESULTS: The age, the parents' salary, the number of siblings aged below 18 years, the presence of rhinitis, ears diseases, the exams, drugs and otological surgeries that were indicated were all statistically significant. CONCLUSION: The most common diagnosis was mouth breathing. The most common surgery was adenotonsillectomy. The most frequently requested exam was a lateral cranial radiograph. The number of unemployed parents, their poor salaries, and the number of siblings make if difficult for these patients to be treated in any facility other than the public heath system.A criação de um banco de dados sobre as demandas otorrinolaringológicas no SUS poderá fornecer informações para organizar estratégias de saúde e criar ou otimizar recursos do governo ou privados. OBJETIVOS: Determinar em pacientes até 17 anos de idade: 1) As principais doenças otorrinolaringológicas diagnosticadas; 2) Exames complementares mais solicitados; 3) Medicamentos mais prescritos; 4) Procedimentos ambulatoriais realizados e as indicações cirúrgicas; 5) Estado empregatício dos pais e o número de irmãos dependentes; 6) Comparar e analisar estatisticamente os dados nos locais estudados. MATERIAL E MÉTODO: Estudo prospectivo e análise estatística das variáveis obtidas nas primeiras-consultas na Policlínica de Mariana, na sede Consórcio Intermunicipal de Saúde da Microrregião de Sete Lagoas e na Triagem da Otorrinolaringologia da UNIFESP-EPM. RESULTADOS: Há diferenças estatisticamente significativas quanto às variáveis idade, média salarial dos pais empregados, número de irmãos até 17 anos, rinite, doenças otológicas, exames solicitados, prescrições e indicações de cirurgias micro-otológicas. CONCLUSÕES: O diagnóstico mais encontrado foi respiração oral. O exame complementar e a cirurgia mais indicados foram a radiografia de cavum e a adenoamigdalectomia. O nível de desemprego, a baixa média salarial e o número de dependentes na família dificultam tratamentos que não estejam disponíveis na rede pública de saúde.Hospital João XXIIIInstituto de Otorrinolaringologia de Minas GeraisUNIFESP-EPM Departamento de Otorrinolaringologia e Cirurgia de Cabeça e PescoçoUNIFESP-EPM Programa de Pós-Graduação em Otorrinolaringologia e Cirurgia de Cabeça e PescoçoUNIFESP, EPM, Depto. de Otorrinolaringologia e Cirurgia de Cabeça e PescoçoUNIFESP, EPM Programa de Pós-Graduação em Otorrinolaringologia e Cirurgia de Cabeça e PescoçoSciEL

The Human Auditory System

This book presents the latest findings in clinical audiology with a strong emphasis on new emerging technologies that facilitate and optimize a better assessment of the patient. The book has been edited with a strong educational perspective (all chapters include an introduction to their corresponding topic and a glossary of terms). The book contains material suitable for graduate students in audiology, ENT, hearing science and neuroscience

Harnessing the power of artificial intelligence to transform hearing healthcare and research

The advances in artificial intelligence that are transforming many fields have yet to make an impact in hearing. Hearing healthcare continues to rely on a labour-intensive service model that fails to provide access to the majority of those in need, while hearing research suffers from a lack of computational tools with the capacity to match the complexities of auditory processing. This Perspective is a call for the artificial intelligence and hearing communities to come together to bring about a technological revolution in hearing. We describe opportunities for rapid clinical impact through the application of existing technologies and propose directions for the development of new technologies to create true artificial auditory systems. There is an urgent need to push hearing towards a future in which artificial intelligence provides critical support for the testing of hypotheses, the development of therapies and the effective delivery of care worldwide