Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies... more Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies are recommended in guidelines for the reduction of tinnitus distress; however, little is known about the potentially increased effectiveness of a combination of treatments and personalized treatments for each tinnitus patient. Methods Within the Unification of Treatments and Interventions for Tinnitus Patients project, a multicenter, randomized clinical trial is conducted with the aim to compare the effectiveness of single treatments and combined treatments on tinnitus distress (UNITI-RCT). Five different tinnitus centers across Europe aim to treat chronic tinnitus patients with either cognitive behavioral therapy, sound therapy, structured counseling, or hearing aids alone, or with a combination of two of these treatments, resulting in four treatment arms with single treatment and six treatment arms with combinational treatment. This statistical analysis plan describes the statistical ...
Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies... more Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies are recommended in guidelines for the reduction of tinnitus distress; however, little is known about the potential increased effectiveness of a combination of treatments and personalized treatments for each tinnitus patient. Methods Within the Uni cation of Treatments and Interventions for Tinnitus Patients project, a multicenter, randomized clinical trial is conducted with the aim to compare the effectiveness of single treatments and combined treatments on tinnitus distress (UNITI-RCT). Five different tinnitus centers across Europe aim to treat chronic tinnitus patients with either cognitive behavior therapy, sound therapy, structured counseling, or hearing aids alone, or with a combination of two of these treatments, resulting in 4 treatment arms with single treatment and 6 treatment arms with combinational treatment. This statistical analysis plan describes the statistical methods to be deployed in the UNITI-RCT. Discussion The UNITI-RCT trial will provide important evidence about whether a combination of treatments is superior to a single treatment alone in the management of chronic tinnitus patients. This pre-speci ed statistical analysis plan details the methodology for the analysis of the UNITI trial results. Trial registration ClinicalTrials.gov NCT04663828 (https://clinicaltrials.gov/ct2/show/NCT04663828). The trial is ongoing. Date of registration: December 11, 2020. The main RCT analyses will start by the end of December 2022 and will include data from patients who have nished their treatment by the 19th of December 2022.
Voice loss constitutes a crucial disorder which is highly associated with social isolation. The u... more Voice loss constitutes a crucial disorder which is highly associated with social isolation. The use of multimodal information sources, such as, audiovisual information, is crucial since it can lead to the development of straightforward personalized word prediction models which can reproduce the patient’s original voice. In this work we designed a multimodal approach based on audiovisual information from patients before loss-of-voice to develop a system for automated lip-reading in the Greek language. Data pre-processing methods, such as, lip-segmentation and frame-level sampling techniques were used to enhance the quality of the imaging data. Audio information was incorporated in the model to automatically annotate sets of frames as words. Recurrent neural networks were trained on four different video recordings to develop a robust word prediction model. The model was able to correctly identify test words in different time frames with 95% accuracy. To our knowledge, this is the first word prediction model that is trained to recognize words from video recordings in the Greek language.
Voice loss constitutes a crucial disorder which is highly associated with social isolation. The u... more Voice loss constitutes a crucial disorder which is highly associated with social isolation. The use of multimodal information sources, such as, audiovisual information, is crucial since it can lead to the development of straightforward personalized word prediction models which can reproduce the patient’s original voice. In this work we designed a multimodal approach based on audiovisual information from patients before loss-of-voice to develop a system for automated lip-reading in the Greek language. Data pre-processing methods, such as, lip-segmentation and frame-level sampling techniques were used to enhance the quality of the imaging data. Audio information was incorporated in the model to automatically annotate sets of frames as words. Recurrent neural networks were trained on four different video recordings to develop a robust word prediction model. The model was able to correctly identify test words in different time frames with 95% accuracy. To our knowledge, this is the firs...
Physical inactivity has a huge socioeconomic cost, with an estimated contribution of 3.7% of heal... more Physical inactivity has a huge socioeconomic cost, with an estimated contribution of 3.7% of health care costs in Canada, and is associated with increased morbidity and
Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies... more Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies are recommended in guidelines for the reduction of tinnitus distress; however, little is known about the potentially increased effectiveness of a combination of treatments and personalized treatments for each tinnitus patient. Methods Within the Unification of Treatments and Interventions for Tinnitus Patients project, a multicenter, randomized clinical trial is conducted with the aim to compare the effectiveness of single treatments and combined treatments on tinnitus distress (UNITI-RCT). Five different tinnitus centers across Europe aim to treat chronic tinnitus patients with either cognitive behavioral therapy, sound therapy, structured counseling, or hearing aids alone, or with a combination of two of these treatments, resulting in four treatment arms with single treatment and six treatment arms with combinational treatment. This statistical analysis plan describes the statistical ...
Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies... more Background Tinnitus is a leading cause of disease burden globally. Several therapeutic strategies are recommended in guidelines for the reduction of tinnitus distress; however, little is known about the potential increased effectiveness of a combination of treatments and personalized treatments for each tinnitus patient. Methods Within the Uni cation of Treatments and Interventions for Tinnitus Patients project, a multicenter, randomized clinical trial is conducted with the aim to compare the effectiveness of single treatments and combined treatments on tinnitus distress (UNITI-RCT). Five different tinnitus centers across Europe aim to treat chronic tinnitus patients with either cognitive behavior therapy, sound therapy, structured counseling, or hearing aids alone, or with a combination of two of these treatments, resulting in 4 treatment arms with single treatment and 6 treatment arms with combinational treatment. This statistical analysis plan describes the statistical methods to be deployed in the UNITI-RCT. Discussion The UNITI-RCT trial will provide important evidence about whether a combination of treatments is superior to a single treatment alone in the management of chronic tinnitus patients. This pre-speci ed statistical analysis plan details the methodology for the analysis of the UNITI trial results. Trial registration ClinicalTrials.gov NCT04663828 (https://clinicaltrials.gov/ct2/show/NCT04663828). The trial is ongoing. Date of registration: December 11, 2020. The main RCT analyses will start by the end of December 2022 and will include data from patients who have nished their treatment by the 19th of December 2022.
Voice loss constitutes a crucial disorder which is highly associated with social isolation. The u... more Voice loss constitutes a crucial disorder which is highly associated with social isolation. The use of multimodal information sources, such as, audiovisual information, is crucial since it can lead to the development of straightforward personalized word prediction models which can reproduce the patient’s original voice. In this work we designed a multimodal approach based on audiovisual information from patients before loss-of-voice to develop a system for automated lip-reading in the Greek language. Data pre-processing methods, such as, lip-segmentation and frame-level sampling techniques were used to enhance the quality of the imaging data. Audio information was incorporated in the model to automatically annotate sets of frames as words. Recurrent neural networks were trained on four different video recordings to develop a robust word prediction model. The model was able to correctly identify test words in different time frames with 95% accuracy. To our knowledge, this is the first word prediction model that is trained to recognize words from video recordings in the Greek language.
Voice loss constitutes a crucial disorder which is highly associated with social isolation. The u... more Voice loss constitutes a crucial disorder which is highly associated with social isolation. The use of multimodal information sources, such as, audiovisual information, is crucial since it can lead to the development of straightforward personalized word prediction models which can reproduce the patient’s original voice. In this work we designed a multimodal approach based on audiovisual information from patients before loss-of-voice to develop a system for automated lip-reading in the Greek language. Data pre-processing methods, such as, lip-segmentation and frame-level sampling techniques were used to enhance the quality of the imaging data. Audio information was incorporated in the model to automatically annotate sets of frames as words. Recurrent neural networks were trained on four different video recordings to develop a robust word prediction model. The model was able to correctly identify test words in different time frames with 95% accuracy. To our knowledge, this is the firs...
Physical inactivity has a huge socioeconomic cost, with an estimated contribution of 3.7% of heal... more Physical inactivity has a huge socioeconomic cost, with an estimated contribution of 3.7% of health care costs in Canada, and is associated with increased morbidity and
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