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Analyzing domain shift when using additional data for the MICCAI KiTS23 Challenge

Using additional training data is known to improve the results, especially for medical image 3D segmentation where there is a lack of training material and the model needs to generalize well from few available data.

Continua a leggereAnalyzing domain shift when using additional data for the MICCAI KiTS23 Challenge

Automated Stabilization, Enhancement and Capillaries Segmentation in Videocapillaroscopy

Oral capillaroscopy is a critical and non-invasive technique used to evaluate microcirculation. Its ability to observe small vessels in vivo has generated significant interest in the field. Capillaroscopy serves as an essential tool for diagnosing and prognosing various pathologies, with anatomic–pathological lesions playing a crucial role in their progression.

Continua a leggereAutomated Stabilization, Enhancement and Capillaries Segmentation in Videocapillaroscopy

Robust and language-independent acoustic features in Parkinson’s disease

The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in supporting early diagnosis and disease monitoring.

Continua a leggereRobust and language-independent acoustic features in Parkinson’s disease

Teeth Segmentation in Panoramic Dental X-ray Using Mask Regional Convolutional Neural Network

Accurate instance segmentation of teeth in panoramic dental X-rays is a challenging task due to variations in tooth morphology and overlapping regions. In this study, we propose a new algorithm, for instance, segmentation of the different teeth in panoramic dental X-rays.

Continua a leggereTeeth Segmentation in Panoramic Dental X-ray Using Mask Regional Convolutional Neural Network

Hallmarks of Parkinson’s disease progression determined by temporal evolution of speech attractors in the reconstructed phase-space

Parkinson’s disease (PD) is one of the most widespread neurodegenerative diseases worldwide, affected by a number of alterations, among which speech impairments that, interestingly, manifests up to 10 years before other major evidences (e.g. motor impairments).

Continua a leggereHallmarks of Parkinson’s disease progression determined by temporal evolution of speech attractors in the reconstructed phase-space

Machine learning- and statistical-based voice analysis of Parkinson’s disease patients: A survey

The preliminary diagnosis and evaluation of the presence and/or severity of Parkinson’s disease is crucial in controlling the progress of the disease.

Continua a leggereMachine learning- and statistical-based voice analysis of Parkinson’s disease patients: A survey

Artificial Intelligence-Based Voice Assessment of Patients with Parkinson’s Disease Off and On Treatment: Machine vs. Deep-Learning Comparison

Parkinson’s Disease (PD) is one of the most common non-curable neurodegenerative diseases. Diagnosis is achieved clinically on the basis of different symptoms with considerable delays from the onset of neurodegenerative processes in the central nervous system.

Continua a leggereArtificial Intelligence-Based Voice Assessment of Patients with Parkinson’s Disease Off and On Treatment: Machine vs. Deep-Learning Comparison

How resistant are levodopa-resistant axial symptoms? Response of freezing, posture, and voice to increasing levodopa intestinal infusion rates in Parkinson disease

Treatment of freezing of gait (FoG) and other Parkinson disease (PD) axial symptoms is challenging. Systematic assessments of axial symptoms at progressively increasing levodopa doses are lacking. We sought to analyze the resistance to high levodopa doses of FoG, posture, speech, and altered gait features presenting in daily-ON therapeutic condition.

Continua a leggereHow resistant are levodopa-resistant axial symptoms? Response of freezing, posture, and voice to increasing levodopa intestinal infusion rates in Parkinson disease

Obesity and Gastro-Esophageal Reflux voice disorders: a Machine Learning approach

Automatic assessment of speech disorders is a cutting-edge topic in vocal analysis. Recent studies indicated possible connections between eating disorders and voice alterations.

Continua a leggereObesity and Gastro-Esophageal Reflux voice disorders: a Machine Learning approach

Recognizing the Emergent and Submerged Iceberg of the Celiac Disease: ITAMA Project — Global Strategy Protocol

Coeliac disease (CD) is frequently underdiagnosed with a consequent heavy burden in terms of morbidity and health care costs. Diagnosis of CD is based on the evaluation of symptoms and anti-transglutaminase antibodies IgA (TGA-IgA) levels, with values above a tenfold increase being the basis of the biopsy-free diagnostic approach suggested by present guidelines.

Continua a leggereRecognizing the Emergent and Submerged Iceberg of the Celiac Disease: ITAMA Project — Global Strategy Protocol

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