AIMC Topic: Machine Learning

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Tendon Stress Estimation from Strain Data of a Bridge Girder Using Machine Learning-Based Surrogate Model.

Sensors (Basel, Switzerland)
Prestressed girders reduce cracking and allow for long spans, but their construction requires complex equipment and strict quality control. Their accurate design depends on a precise knowledge of tensioning force and stresses, as well as monitoring t...

The artificial intelligence and machine learning in lung cancer immunotherapy.

Journal of hematology & oncology
Since the past decades, more lung cancer patients have been experiencing lasting benefits from immunotherapy. It is imperative to accurately and intelligently select appropriate patients for immunotherapy or predict the immunotherapy efficacy. In rec...

Embracing cohort heterogeneity in clinical machine learning development: a step toward generalizable models.

Scientific reports
This study is a simple illustration of the benefit of averaging over cohorts, rather than developing a prediction model from a single cohort. We show that models trained on data from multiple cohorts can perform significantly better in new settings t...

Higher depression risks in medium- than in high-density urban form across Denmark.

Science advances
Urban areas are associated with higher depression risks than rural areas. However, less is known about how different types of urban environments relate to depression risk. Here, we use satellite imagery and machine learning to quantify three-dimensio...

Machine learning and classical MD simulation to identify inhibitors against the P37 envelope protein of monkeypox virus.

Journal of biomolecular structure & dynamics
Monkeypox virus (MPXV) outbreak is a serious public health concern that requires international attention. P37 of MPXV plays a pivotal role in DNA replication and acts as one of the promising targets for antiviral drug design. In this study, we intent...

AI and machine learning ethics, law, diversity, and global impact.

The British journal of radiology
Artificial intelligence (AI) and its machine learning (ML) algorithms are offering new promise for personalized biomedicine and more cost-effective healthcare with impressive technical capability to mimic human cognitive capabilities. However, widesp...

Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.

Medical image analysis
Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concerning brain research as well as clinical practice. For this reason, several machine learning-based methods have been developed for the automatic qualit...

A novel gluten knowledge base of potential biomedical and health-related interactions extracted from the literature: Using machine learning and graph analysis methodologies to reconstruct the bibliome.

Journal of biomedical informatics
BACKGROUND: In return for their nutritional properties and broad availability, cereal crops have been associated with different alimentary disorders and symptoms, with the majority of the responsibility being attributed to gluten. Therefore, the rese...

On modeling the correlates of conspiracy thinking.

Scientific reports
While a robust literature on the psychology of conspiracy theories has identified dozens of characteristics correlated with conspiracy theory beliefs, much less attention has been paid to understanding the generalized predisposition towards interpret...

Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective.

Journal of chemical information and modeling
Absorption, distribution, metabolism, and excretion (ADME), which collectively define the concentration profile of a drug at the site of action, are of critical importance to the success of a drug candidate. Recent advances in machine learning algori...