AIMC Topic: Algorithms

Clear Filters Showing 24111 to 24120 of 28713 articles

External validation of a proprietary risk model for 1-year mortality in community-dwelling adults aged 65 years or older.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To examine the discrimination, calibration, and algorithmic fairness of the Epic End of Life Care Index (EOL-CI).

Discover important donor-recipient risk factors and interactions in heart transplant primary graft dysfunction with machine learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Primary graft dysfunction (PGD) is an essential outcome after the heart transplant, which causes severe complications and symptoms for recipients. The in advance prediction of PGD can help the transplant physician better manage the risks ...

Human visual perception-inspired medical image segmentation network with multi-feature compression.

Artificial intelligence in medicine
Medical image segmentation is crucial for computer-aided diagnosis and treatment planning, directly influencing clinical decision-making. To enhance segmentation accuracy, existing methods typically fuse local, global, and various other features. How...

A Novel Linear Machine Learning Method Based on DNA Hybridization Reaction Circuit.

IEEE transactions on nanobioscience
DNA hybridization reaction is a significant technology in the field of semi-synthetic biology and holds great potential for use in biological computation. In this study, we propose a novel machine learning model based on a DNA hybridization reaction ...

Wet and dry cough classification using cough sound characteristics and machine learning: A systematic review.

International journal of medical informatics
BACKGROUND: Distinguishing between productive (wet) and non-productive (dry) cough types is important for evaluating respiratory health, assisting in differential diagnosis, and monitoring disease progression. However, assessing cough type through th...

A systematic review of generative AI approaches for medical image enhancement: Comparing GANs, transformers, and diffusion models.

International journal of medical informatics
BACKGROUND: Medical imaging is a vital diagnostic tool that provides detailed insights into human anatomy but faces challenges affecting its accuracy and efficiency. Advanced generative AI models offer promising solutions. Unlike previous reviews wit...

Comparing logistic regression and machine learning for obesity risk prediction: A systematic review and meta-analysis.

International journal of medical informatics
BACKGROUND: Logistic regression (LR) has traditionally been the standard method used for predicting binary health outcomes; however, machine learning (ML) methods are increasingly popular.

Mathematical expression exploration with graph representation and generative graph neural network.

Neural networks : the official journal of the International Neural Network Society
Symbolic Regression (SR) methods in tree representations have exhibited commendable outcomes across Genetic Programming (GP) and deep learning search paradigms. Nonetheless, the tree representation of mathematical expressions occasionally embodies re...

Motif and supernode-enhanced gated graph neural networks for session-based recommendation.

Neural networks : the official journal of the International Neural Network Society
Session-based recommendation systems aim to predict users' next interactions based on short-lived, anonymous sessions, a challenging yet vital task due to the sparsity and dynamic nature of user behavior. Existing Graph Neural Network (GNN)-based met...

Construction and verification of risk prediction model for suicidal attempts of mood disorder based on machine learning.

Journal of affective disorders
BACKGROUND: Mood disorders (MD) are closely related to suicide attempt (SA). Developing an effective prediction model for SA in MD patients could play a crucial role in the early identification of high-risk groups.