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Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning.

Nature communications
The increasing complexity of lung surgeries necessitates the need for enhanced imaging support to improve the precision and efficiency of preoperative planning. Despite the promise of 3D reconstruction, clinical adoption remains limited due to time c...

A hybrid approach for binary and multi-class classification of voice disorders using a pre-trained model and ensemble classifiers.

BMC medical informatics and decision making
Recent advances in artificial intelligence-based audio and speech processing have increasingly focused on the binary and multi-class classification of voice disorders. Despite progress, achieving high accuracy in multi-class classification remains ch...

Machine Learning Assisted Stroke Prediction in Mechanical Circulatory Support: Predictive Role of Systemic Mitochondrial Dysfunction.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
Stroke continues to be a major adverse event in advanced congestive heart failure (CHF) patients after continuous-flow left ventricular assist device (CF-LVAD) implantation. Abnormalities in mitochondrial oxidative phosphorylation (OxPhos) have been ...

Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study.

European journal of neurology
BACKGROUND: Postural instability and gait difficulties are key symptoms of Parkinson's disease (PD), elevating the risk of falls substantially. Falls afflict 35% to 90% of PD patients, representing a major challenge in managing the condition. Accurat...

Oxidative Phosphorylation Pathway in Ankylosing Spondylitis: Multi-Omics Analysis and Machine Learning.

International journal of rheumatic diseases
INTRODUCTION: Ankylosing spondylitis (AS) is a chronic inflammatory disease affecting the axial skeleton, characterized by immune microenvironment dysregulation and elevated cytokines like TNF-α and IL-17. Mitochondrial oxidative phosphorylation (OXP...

Light Bladder Net: Non-invasive Bladder Cancer Prediction by Weighted Deep Learning Approaches and Graphical Data Transformation.

Anticancer research
BACKGROUND/AIM: Bladder cancer (BCa) is associated with high recurrence rates, emphasizing the importance of early and accurate detection. This study aimed to develop a lightweight and fast deep learning model, Light-Bladder-Net (LBN), for non-invasi...

Exploring Patient Experiences With and Perceptions of Robotic-Assisted Surgery in Denmark.

AORN journal
Although the use of robotic-assisted surgery (RAS) is increasing worldwide, qualitative research on the patient experience with RAS is lacking. To understand patients' perioperative experiences, the authors conducted semi-structured interviews with f...