AIMC Topic: Adult

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Enhancing the Diagnostic Accuracy of Sacroiliitis: A Machine Learning Approach Applied to Computed Tomography Imaging.

British journal of hospital medicine (London, England : 2005)
Sacroiliitis is a challenging condition to diagnose accurately due to the subtle nature of its presentation in imaging studies. This study aims to improve the diagnostic accuracy of sacroiliitis by applying advanced machine learning techniques to co...

Identifying Elective Induction of Labor among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Health Care System.

American journal of perinatology
OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...

Developmental and Validation of Machine Learning Model for Prediction Complication After Cervical Spine Metastases Surgery.

Clinical spine surgery
STUDY DESIGN: This is a retrospective cohort study utilizing machine learning to predict postoperative complications in cervical spine metastases surgery.

Looking into the future: a machine learning powered prediction model for oocyte return rates after cryopreservation.

Reproductive biomedicine online
RESEARCH QUESTION: Could a predictive model, using data from all US fertility clinics reporting to the Society for Assisted Reproductive Technology, estimate the likelihood of patients using their stored oocytes?

Machine Learning Model Reveals Determinators for Admission to Acute Mental Health Wards From Emergency Department Presentations.

International journal of mental health nursing
This research addresses the critical issue of identifying factors contributing to admissions to acute mental health (MH) wards for individuals presenting to the emergency department (ED) with MH concerns as their primary issue, notably suicidality. T...

Deep learning to predict risk of lateral skull base cerebrospinal fluid leak or encephalocele.

International journal of computer assisted radiology and surgery
PURPOSE: Skull base features, including increased foramen ovale (FO) cross-sectional area, are associated with lateral skull base spontaneous cerebrospinal fluid (sCSF) leak and encephalocele. Manual measurement requires skill in interpreting imaging...

Construction and evaluation of a predictive model for the types of sleep respiratory events in patients with OSA based on hypoxic parameters.

Sleep & breathing = Schlaf & Atmung
OBJECTIVE: To explore the differences and associations of hypoxic parameters among distinct types of respiratory events in patients with obstructive sleep apnea (OSA) and to construct prediction models for the types of respiratory events based on hyp...

SAD: semi-supervised automatic detection of BOLD activations in high temporal resolution fMRI data.

Magma (New York, N.Y.)
OBJECTIVE: Despite the prevalent use of the general linear model (GLM) in fMRI data analysis, assuming a pre-defined hemodynamic response function (HRF) for all voxels can lead to reduced reliability and may distort the inferences derived from it. To...

A deep learning approach for cervical cord injury severity determination through axial and sagittal magnetic resonance imaging segmentation and classification.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
STUDY DESIGN: Cross-sectional Database Study.

Artificial neural network inference analysis identified novel genes and gene interactions associated with skeletal muscle aging.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Sarcopenia is an age-related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased muscle protein degradation driven by molecular signalling pathways including Akt and FOXO1. This study ...