AIMC Topic: Male

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Protocol for the REBOUND study: a cohort study to uncover fundamental mechanisms of accelerated ageing and impaired resilience following cancer surgery and treatment.

BMC geriatrics
BACKGROUND: Ageing is a heterogeneous process, which is associated with heterogeneous resilience in older people. Cancer surgery and treatment may be associated with accelerated ageing in some older people; studying this process will improve understa...

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in trauma-induced coagulopathy.

Scientific reports
Despite advancements in trauma care, uncontrolled hemorrhage and trauma-induced coagulopathy (TIC) remain the leading causes of preventable deaths after trauma. Understanding the genetic underpinnings and molecular mechanisms of TIC is crucial for de...

Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data.

Scientific reports
Keratoconus is a progressive eye disease characterized by the thinning and bulging of the cornea, leading to visual impairment. Early and accurate diagnosis is crucial for effective management and treatment. This study investigates the application of...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Scientific reports
Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-based non-invasive tests (NIT) cannot yet reliably predict MASLD outcomes. The role of B-mode ultrasound...

AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view.

Scientific reports
This study aims to enhance the dosimetry accuracy in I planar imaging by utilizing a single oblique view and Monte Carlo (MC) validated dose point kernels (DPKs) alongside the integration of artificial intelligence (AI) for accurate dose prediction w...

Multi-task reinforcement learning and explainable AI-Driven platform for personalized planning and clinical decision support in orthodontic-orthognathic treatment.

Scientific reports
This study presents a novel clinical decision support platform for orthodontic-orthognathic treatment that integrates multi-task reinforcement learning with explainable artificial intelligence. The platform addresses the challenges of personalized tr...

Integrating radiomic texture analysis and deep learning for automated myocardial infarction detection in cine-MRI.

Scientific reports
Robust differentiation between infarcted and normal myocardial tissue is essential for improving diagnostic accuracy and personalizing treatment in myocardial infarction (MI). This study proposes a hybrid framework combining radiomic texture analysis...

Deep learning diagnosis plus kinematic severity assessments of neurodivergent disorders.

Scientific reports
Early diagnostic assessments of neurodivergent disorders (NDD), remains a major clinical challenge. We address this problem by pursuing the hypothesis that there is important cognitive information about NDD conditions contained in the way individuals...

Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets.

Scientific reports
The treatment of sepsis is challenging due to unclear mechanisms. Propionate is increasingly seen as critical to sepsis pathophysiology by bridging gut microbiota and immunity, but the mechanisms remain unclear. Our study analysed differences in prop...

Lossy DICOM conversion may affect AI performance.

Scientific reports
Many pathologies have started to digitize their glass slides. To ensure long term accessibility, it is desirable to store them in the DICOM format. Currently, many scanners initially store the images in vendor-specific formats and only provide DICOM ...