Results 101 to 110 of about 56,067 (285)
On Automation and Medical Image Interpretation, With Applications for Laryngeal Imaging [PDF]
arXiv, 2012 Indeed, these are exciting times. We are in the heart of a digital renaissance. Automation and computer technology allow engineers and scientists to fabricate processes that amalgamate quality of life. We anticipate much growth in medical image interpretation and understanding, due to the influx of computer technologies.
arxiv
Head &Neck, EarlyView.ABSTRACT Background Time from surgery to initiation of postoperative radiation therapy (PORT) of less than 6 weeks was recently instituted as the first quality metric within head and neck cancer care. Methods We performed a retrospective single institution cohort study to investigate predictors of PORT delay and the impact of PORT delay on survival ...
Niketna Vivek +10 more
wiley +1 more source
The Accuracy of Patient History, Wheezing, and Laryngeal Measurements in Diagnosing Obstructive Airway Disease [PDF]
, 2000 Sharon E. Straus
openalex +1 more source
Glottal Closure Instants Detection From Pathological Acoustic Speech Signal Using Deep Learning [PDF]
arXiv, 2018 In this paper, we propose a classification based glottal closure instants (GCI) detection from pathological acoustic speech signal, which finds many applications in vocal disorder analysis. Till date, GCI for pathological disorder is extracted from laryngeal (glottal source) signal recorded from Electroglottograph, a dedicated device designed to ...
arxiv
Head &Neck, EarlyView.ABSTRACT Background Globally, most people with head and neck cancers (HNCs) are diagnosed with advanced‐stage disease. HNC diagnostic stage has multifactorial explanations, with the role of health system factors not yet fully investigated. Methods HNC centres (n = 18) from the HEADSpAcE Consortium were surveyed via a bespoke health system questionnaire
Grant Creaney +201 more
wiley +1 more source
Parameterization of Sequence of MFCCs for DNN-based voice disorder detection [PDF]
arXiv, 2018 In this article a DNN-based system for detection of three common voice disorders (vocal nodules, polyps and cysts; laryngeal neoplasm; unilateral vocal paralysis) is presented. The input to the algorithm is (at least 3-second long) audio recording of sustained vowel sound /a:/. The algorithm was developed as part of the "2018 FEMH Voice Data Challenge"
arxiv
Factors Increasing the Likelihood of Postoperative Hematomas Following Thyroid Surgery
Head &Neck, EarlyView.ABSTRACT Background Neck hematoma following thyroid surgery is a potentially life‐threatening complication. Methods This retrospective case–control study reviewed neck hematoma reoperations following thyroid surgery (2009–2024), using 3:1 matching. Univariable analysis identified hematoma and delayed onset (≥ 6 h) risk factors, with odds ratios (ORs ...
Emily Ajit‐Roger +9 more
wiley +1 more source
A Comparative Study of Pitch Extraction Algorithms on a Large Variety of Singing Sounds [PDF]
arXiv, 2019 The problem of pitch tracking has been extensively studied in the speech research community. The goal of this paper is to investigate how these techniques should be adapted to singing voice analysis, and to provide a comparative evaluation of the most representative state-of-the-art approaches. This study is carried out on a large database of annotated
arxiv
Prognosis and Phenotypes of Advanced Head and Neck Carcinoma Associated With Hypercalcemia
Head &Neck, EarlyView.ABSTRACT Purpose Hypercalcemia is the most common metabolic disorder in cancer, affecting 10%–20% of patients with advanced malignancies, including squamous cell carcinoma of the head and neck (HNSCC), though its prognostic significance remains poorly studied.
Elodie Mamou +5 more
wiley +1 more source