AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Regression Analysis

Showing 261 to 270 of 415 articles

Clear Filters

A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm.

Biomechanics and modeling in mechanobiology
Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused on relationship between intuitive geometric features (e.g., diam...

Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the osteoarthritis initiative.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
UNLABELLED: The purpose of this study is to evaluate the ability of a machine learning algorithm to classify in vivo magnetic resonance images (MRI) of human articular cartilage for development of osteoarthritis (OA). Sixty-eight subjects were select...

A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare.

IEEE journal of biomedical and health informatics
Health analysis often involves prediction of multiple outcomes of mixed type. The existing work is restrictive to either a limited number or specific outcome types. We propose a framework for mixed-type multioutcome prediction. Our proposed framework...

Mobile Stride Length Estimation With Deep Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
OBJECTIVE: Accurate estimation of spatial gait characteristics is critical to assess motor impairments resulting from neurological or musculoskeletal disease. Currently, however, methodological constraints limit clinical applicability of state-of-the...

Leveraging electronic health records for predictive modeling of post-surgical complications.

Statistical methods in medical research
Hospital-specific electronic health record systems are used to inform clinical practice about best practices and quality improvements. Many surgical centers have developed deterministic clinical decision rules to discover adverse events (e.g. postope...

Predictability and interpretability of hybrid link-level crash frequency models for urban arterials compared to cluster-based and general negative binomial regression models.

International journal of injury control and safety promotion
Machine learning (ML) techniques have higher prediction accuracy compared to conventional statistical methods for crash frequency modelling. However, their black-box nature limits the interpretability. The objective of this research is to combine bot...

Predicting Prolonged Stay in the ICU Attributable to Bleeding in Patients Offered Plasma Transfusion.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In blood transfusion studies, plasma transfusion (PPT) and bleeding are known to be associated with risk of prolonged ICU length of stay (ICU-LOS). However, as patients can show significant heterogeneity in response to a treatment, there might exists...

Artificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitis.

Journal of thrombosis and haemostasis : JTH
UNLABELLED: Essentials Predicting the occurrence of portosplenomesenteric vein thrombosis (PSMVT) is difficult. We studied 72 patients with acute pancreatitis. Artificial neural networks modeling was more accurate than logistic regression in predicti...

Deep ensemble learning of sparse regression models for brain disease diagnosis.

Medical image analysis
Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effecti...

A novel multi-target regression framework for time-series prediction of drug efficacy.

Scientific reports
Excavating from small samples is a challenging pharmacokinetic problem, where statistical methods can be applied. Pharmacokinetic data is special due to the small samples of high dimensionality, which makes it difficult to adopt conventional methods ...