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Parkinson disease detection based on in-air dynamics feature extraction and selection using machine learning.

Scientific reports
Parkinson's disease (PD) is a progressive neurological disorder that impairs movement control, leading to symptoms such as tremors, stiffness, and bradykinesia. Early and accurate PD detection is essential for effective management and improving patie...

Retrospective study of onychomycosis patients treated with ciclopirox 8% HPCH and oral antifungals applying artificial intelligence to electronic health records.

Scientific reports
We conducted a multicenter retrospective analysis of 408 patients diagnosed with onychomycosis who attended three tertiary care Spanish hospitals. The study was conducted to assess the clinical characteristics and outcomes of onychomycosis patients u...

AI-assisted intraoperative navigation for safe right liver mobilization in pure laparoscopic donor hepatectomy: an experimental multi-institutional validation study.

Scientific reports
Minimally invasive liver surgery (MILS) offers significant benefits but faces limited adoption due to its steep learning curve. This study explores the potential of artificial intelligence (AI) in assisting the performance of major MILS by providing ...

Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation.

Nature communications
Atrial fibrillation (AF) increases the risk of adverse cardiovascular events, yet the underlying biological mechanisms remain unclear. We evaluate a panel of 12 circulating biomarkers representing diverse pathophysiological pathways in 3817 AF patien...

Mitochondrial Pathway Signature (MitoPS) predicts immunotherapy response and reveals NDUFB10 as a key immune regulator in lung adenocarcinoma.

Journal for immunotherapy of cancer
BACKGROUND: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Although immune checkpoint inhibitors (ICIs) have brought new treatment options for advanced patients, a considerable proportion still shows limited resp...

Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study.

JMIR research protocols
BACKGROUND: Depression is a mental health condition that affects millions of people worldwide. Although common, it remains difficult to diagnose due to its heterogeneous symptomatology. Mental health questionnaires are currently the most used assessm...

Large language models for extraction of OPS-codes from operative reports in meningioma surgery.

Acta neurochirurgica
BACKGROUND: In the German medical billing system, surgical departments encode their procedures in OPS-codes. These OPS-codes have major impact on DRG grouping and thus mainly determine each case“s revenue. In our study, we investigate the ability of ...

Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data.

Scientific reports
Myocardial infarction (MI) remains one of the greatest contributors to mortality, and patients admitted to the intensive care unit (ICU) with myocardial infarction are at higher risk of death. In this study, we use two retrospective cohorts extracted...

AI-Driven fetal distress monitoring SDN-IoMT networks.

PloS one
The healthcare industry is transforming with the integration of the Internet of Medical Things (IoMT) with AI-powered networks for improved clinical connectivity and advanced monitoring capabilities. However, IoMT devices struggle with traditional ne...

Uncovering locomotor learning dynamics in people with Parkinson's disease.

PloS one
Locomotor learning is important for improving gait and balance impairments in people with Parkinson's disease (PD). While PD disrupts neural networks involved in motor learning, there is a limited understanding of how PD influences the time course of...