AIMC Topic: Registries
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Predicting opportunities for improvement in trauma care using machine learning: a retrospective registry-based study at a major trauma centre.
BMJ open
Jun 6, 2025
OBJECTIVE: To develop models to predict opportunities for improvement in trauma care and compare the performance of these models to the currently used audit filters.
Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxiety.
BMC psychiatry
May 30, 2025
BACKGROUND: Internet-delivered cognitive behavioural therapy (ICBT) is an effective and accessible treatment for mild to moderate depression and anxiety disorders. However, up to 50% of patients do not achieve sufficient symptom relief. Identifying p...
Menopausal hormone therapy and the female brain: Leveraging neuroimaging and prescription registry data from the UK Biobank cohort.
eLife
May 29, 2025
BACKGROUND: Menopausal hormone therapy (MHT) is generally thought to be neuroprotective, yet results have been inconsistent. Here, we present a comprehensive study of MHT use and brain characteristics in females from the UK Biobank.
Automated extraction of functional biomarkers of verbal and ambulatory ability from multi-institutional clinical notes using large language models.
Journal of neurodevelopmental disorders
Apr 30, 2025
BACKGROUND: Functional biomarkers in neurodevelopmental disorders, such as verbal and ambulatory abilities, are essential for clinical care and research activities. Treatment planning, intervention monitoring, and identifying comorbid conditions in i...
Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis.
BMJ open
Apr 27, 2025
OBJECTIVE: In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates and limited prediction tools. Despite advances in resuscitation, predicting 30-day survival remains difficult, and current methods lack interpretabilit...
Prescription data and demographics: An explainable machine learning exploration of colorectal cancer risk factors based on data from Danish national registries.
Computer methods and programs in biomedicine
Apr 24, 2025
OBJECTIVES: Despite substantial advancements in both treatment and prevention, colorectal cancer continues to be a leading cause of global morbidity and mortality. This study investigated the potential of using demographics and prescribed drug inform...
Predictive Analysis of Amyotrophic Lateral Sclerosis Progression and Mortality in a Clinic Cohort From Singapore.
Muscle & nerve
Apr 23, 2025
INTRODUCTION: There is currently no comprehensive Amyotrophic Lateral Sclerosis (ALS) patient database in Singapore comparable to those available in Europe and the United States. We established the Singapore ALS registry (SingALS) to draw meaningful ...
Machine Learning Models for Predicting Type 2 Diabetes Complications in Malaysia.
Asia-Pacific journal of public health
Apr 18, 2025
This study aimed to develop machine learning (ML) models to predict diabetic complications in patients with type 2 diabetes (T2D) in Malaysia. Data from the Malaysian National Diabetes Registry and Death Register were used to develop predictive model...
Machine learning center-specific models show improved IVF live birth predictions over US national registry-based model.
Nature communications
Apr 17, 2025
Expanding in vitro fertilization (IVF) access requires improved patient counseling and affordability via cost-success transparency. Clinicians ask how two types of live birth prediction (LBP) models perform: machine learning, center-specific (MLCS) m...
Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.
Scientific reports
Apr 7, 2025
Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history,...
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