The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exception. By synthesizing the existing literature, this review seeks to inform clinicians, researchers, and policymakers about the potential and challenges of integrating AI into audiological practice. The PubMed, Cochrane, and Google Scholar databases were searched for articles published in English from 1990 to 2024 with the following query: “(audiology) AND (“artificial intelligence” OR “machine learning” OR “deep learning”)”. The PRISMA extension for scoping reviews (PRISMA-ScR) was followed. The database research yielded 1359 results, and the selection process led to the inclusion of 104 manuscripts. The integration of AI in audiology has evolved significantly over the succeeding decades, with 87.5% of manuscripts published in the last 4 years. Most types of AI were consistently used for specific purposes, such as logistic regression and other statistical machine learning tools (e.g., support vector machine, multilayer perceptron, random forest, deep belief network, decision tree, k-nearest neighbor, or LASSO) for automated audiometry and clinical predictions; convolutional neural networks for radiological image analysis; and large language models for automatic generation of diagnostic reports. Despite the advances in AI technologies, different ethical and professional challenges are still present, underscoring the need for larger, more diverse data collection and bioethics studies in the field of audiology.

Conclusions. Diagnostic work-up should include contrast-enhanced computed tomography (CT) and mandible orthopantogram. When a dental origin of deep neck infection is suspected, the intravenous antibiotic regimen has to be active against gram-positive bacteria, both aerobes and anaerobes. Surgical exploration and drainage may be mandatory at presentation, or in cases not responding to medical therapy within the first 24 h. Objectives. Deep neck infections are still associated with significant morbidity and mortality rates when complications occur. Despite worldwide improvement in dental care and oral hygiene, a significant prevalence of deep neck infections caused by dental infections has been described recently (>40%). Patients and methods. We analysed retrospectively 85 cases of deep neck infection with dental origin out of 206 consecutive cases of deep neck infection diagnosed in our institution between 2000 and 2006. Results. The most frequent dental source was a periapical infection of the first mandibular molar, followed by second and third molar, respectively. Submandibular space infection involvement was diagnosed in 73 of 85 patients (85.9%), masticatory space infection in 28 (32.9%); in 56 patients (65.9%) the infection involved more than one space. Twenty-four patients (28.2%) were treated only with intravenous antibiotic therapy; 61 patients (71.8%) required both medical and surgical procedures.