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Machine learning models for predicting tibial intramedullary nail length.
BMC musculoskeletal disorders
Apr 21, 2025
BACKGROUND: Tibial intramedullary nailing (IMN) represents a standard treatment for fractures of the tibial shaft. Nevertheless, accurately predicting the appropriate nail length prior to surgery remains a challenging endeavour. Conventional techniqu...
A machine learning model for predicting acute respiratory distress syndrome risk in patients with sepsis using circulating immune cell parameters: a retrospective study.
BMC infectious diseases
Apr 21, 2025
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe complication associated with a high mortality rate in patients with sepsis. Early identification of patients with sepsis at high risk of developing ARDS is crucial for timely interven...
Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data.
Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Apr 20, 2025
BACKGROUND: Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a m...
Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.
Computer methods and programs in biomedicine
Apr 20, 2025
BACKGROUND: It is unclear, whether photoplethysmography (PPG) waveforms from wearable devices can differentiate between supraventricular and ventricular arrhythmias. We assessed, whether a neural network-based classifier can distinguish the origin of...
A Deep Learning Survival Model for Evaluating the Survival Prognosis of Papillary Thyroid Cancer: A Population-Based Cohort Study.
Annals of surgical oncology
Apr 20, 2025
BACKGROUND: Deep learning can assess the individual survival prognosis in sizeable datasets with intricate underlying processes. However, studies exploring the performance of deep learning survival in papillary thyroid cancer (PTC) are lacking. This ...
Protocol of the pilot study to test and evaluate the iCARE tool: a machine learning-based e-platform tool to make health prognoses and support decision-making for the care of older persons with complex chronic conditions.
BMJ open
Apr 19, 2025
INTRODUCTION: The provision of optimal care for older adults with complex chronic conditions (CCCs) poses significant challenges due to the interplay of multiple medical, pharmacological, functional and psychosocial factors. To address these challeng...
Explainable machine learning for predicting lung metastasis of colorectal cancer.
Scientific reports
Apr 19, 2025
Patients with lung metastasis of colorectal cancer typically have a poor prognosis. Therefore, establishing an effective screening and diagnosis model is paramount. Our study seeks to construct and verify a predictive model utilizing machine learning...
Deep learning unlocks the true potential of organ donation after circulatory death with accurate prediction of time-to-death.
Scientific reports
Apr 19, 2025
Increasing the number of organ donations after circulatory death (DCD) has been identified as one of the most important ways of addressing the ongoing organ shortage. While recent technological advances in organ transplantation have increased their s...
Prediction of early recurrence in primary central nervous system lymphoma based on multimodal MRI-based radiomics: A preliminary study.
European journal of radiology
Apr 18, 2025
OBJECTIVES: To evaluate the role of multimodal magnetic resonance imaging radiomics features in predicting early recurrence of primary central nervous system lymphoma (PCNSL) and to investigate their correlation with patient prognosis.
Machine Learning-Based Diagnostic Prediction Model Using T1-Weighted Striatal Magnetic Resonance Imaging for Early-Stage Parkinson's Disease Detection.
Academic radiology
Apr 18, 2025
RATIONALE AND OBJECTIVES: Diagnosing Parkinson's disease (PD) typically relies on clinical evaluations, often detecting it in advanced stages. Recently, artificial intelligence has increasingly been applied to imaging for neurodegenerative disorders....
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