AIMC Topic: Machine Learning

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Retention time prediction for small samples based on integrating molecular representations and adaptive network.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Retention time (RT) can provide orthogonal information different from that of mass spectrometry and contribute to identifying compounds. Many machine learning methods have been developed and applied to RT prediction. In application, the training data...

Use of semi-synthetic data for catheter segmentation improvement.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In the era of data-driven machine learning algorithms, data is the new oil. For the most optimal results, datasets should be large, heterogeneous and, crucially, correctly labeled. However, data collection and labeling are time-consuming and labor-in...

Interpretable machine learning for dementia: A systematic review.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Machine learning research into automated dementia diagnosis is becoming increasingly popular but so far has had limited clinical impact. A key challenge is building robust and generalizable models that generate decisions that can be rel...

Multi-relational graph convolutional networks: Generalization guarantees and experiments.

Neural networks : the official journal of the International Neural Network Society
The class of multi-relational graph convolutional networks (MRGCNs) is a recent extension of standard graph convolutional networks (GCNs) to handle heterogenous graphs with multiple types of relationships. MRGCNs have been shown to yield results supe...

Artificial Intelligence and Machine Learning Approaches to Facilitate Therapeutic Drug Management and Model-Informed Precision Dosing.

Therapeutic drug monitoring
BACKGROUND: Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have greatly benefitted from computational and mathematical advances over the past 60 years. Furthermore, the use of artificial intelligence (AI) and machine lea...

General Graph Neural Network-Based Model To Accurately Predict Cocrystal Density and Insight from Data Quality and Feature Representation.

Journal of chemical information and modeling
Cocrystal engineering as an effective way to modify solid-state properties has inspired great interest from diverse material fields while cocrystal density is an important property closely correlated with the material function. In order to accurately...

Evaluation of AIML + HDR-A Course to Enhance Data Science Workforce Capacity for Hispanic Biomedical Researchers.

International journal of environmental research and public health
Artificial intelligence (AI) and machine learning (ML) facilitate the creation of revolutionary medical techniques. Unfortunately, biases in current AI and ML approaches are perpetuating minority health inequity. One of the strategies to solve this p...

Machine learning to improve frequent emergency department use prediction: a retrospective cohort study.

Scientific reports
Frequent emergency department use is associated with many adverse events, such as increased risk for hospitalization and mortality. Frequent users have complex needs and associated factors are commonly evaluated using logistic regression. However, ot...