Explainable artificial intelligence (XAI) has gained much interest in recent years for its ability
to explain the complex decision-making process of machine learning (ML) and deep …

Alzheimer's disease (AD) stands as a formidable neurodegenerative ailment that poses a
substantial threat to the elderly population, with no known curative or disease-slowing drugs …

Background Heart failure (HF), a global health challenge, requires innovative diagnostic and
management approaches. The rapid evolution of deep learning (DL) in healthcare …

Mild Cognitive Impairment (MCI) is a cognitive state frequently observed in older adults,
characterized by significant alterations in memory, thinking, and reasoning abilities that …

This study explores the possibility of facilitating algorithmic decision-making by combining
interpretable artificial intelligence (XAI) techniques with sensor data, with the aim of …

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges
worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms …

This project was part of the FinnBrain Birth Cohort Study. The main goal of the FinnBrain
study is to advance our understanding of how prenatal (before birth) and early life …

Alzheimer's disease (AD) is a chronic and irreversible neurological disorder, making early
detection essential for managing its progression. This study investigates the coherence of …

Background The relationship between the impact of anti-involution training on critical
thinking and its propensity indicators among young healthcare professionals in dental …

Objective To develop and validate a radiomic-clinical model to assess early cognitive
impairment in type 2 diabetes mellitus (T2DM) using the XGBoost algorithm. Methods We …