Here, we investigated whether incorporating EEG data from overt (pronounced) speech could enhance imagined speech classification. Our approach systematically compares four classification scenarios by ...

This post hoc analysis aimed to identify hypothesis-free PsA phenotype clusters using machine learning to analyse data from the phase III DISCOVER-1/DISCOVER-2 clinical trials. Methods Pooled data ...

Because voice and speech disorders often manifest in patients with PD as early as five years before gross motor dysfunctions, the development of speech-based machine learning (ML) systems has emerged ...

[1] A new hybrid approach based on AOA, CNN and feature fusion that can automatically diagnose Parkinson's disease from sound signals: PDD-AOA-CNN ...

diagrams to represent structural characteristics of data. However, ER diagrams lack the capability to capture the flow and transformation of data through analytic pipelines, which are essential to ...

Early identification of patients at risk of PPD could improve proactive mental health support. Mass General Brigham researchers developed a machine learning model that can evaluate patients' PPD ...

Early identification of patients at risk of PPD could improve proactive mental health support. Researchers developed a machine learning model ... including data on demographics, medical conditions ...

“We continue to collect NfL biomarker data … in ALS patients, which we still plan to analyze in the third quarter of 2025,” Rob Etherington, president and CEO of Clene, said in a company press release ...

The first stage collaboratively augments the training dataset by generating static data and high-quality synthetic speech samples using a natural text-to-speech model (Tacotron2). The second stage ...