AIMC Topic: Machine Learning

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A Framework for Evaluating the Use of Surveillance Systems for Short-Term Influenza Forecasting.

Influenza and other respiratory viruses
BACKGROUND: Public health surveillance systems need to monitor influenza activity and guide measures to mitigate its high impact on morbidity, mortality and healthcare systems. There is an increasing expectation that surveillance data will support th...

Using Machine Learning to Improve Control for Confounding in the Dynamic Weighted Ordinary Least Squares Estimator of Optimal Adaptive Treatment Strategies.

Biometrical journal. Biometrische Zeitschrift
Estimating optimal adaptive treatment strategies (ATSs) can be done in several ways, including dynamic weighted ordinary least squares (dWOLS). This approach is doubly robust as it requires modeling both the treatment and the response, but only one o...

Premolar Ecomorphology in Anthropoid Primates: A Machine Learning Approach.

Journal of morphology
Reconstructing the diets of extinct taxa is essential for understanding their ecologies and evolutionary histories, yet traditional methods and proxies such as molar morphology have limited resolution. The potential of premolar morphology as a dietar...

[Artificial intelligence for randomized controlled trials in cardiology: applications and future perspectives].

Giornale italiano di cardiologia (2006)
Integrating artificial intelligence (AI) into cardiovascular clinical trials is emerging as a key factor in streamlining patient selection, data collection, endpoint monitoring, and outcome analysis. On the one hand, machine learning and deep learnin...

Glucagon-like Peptide-1 Receptor Agonists in Asthma Exacerbations: An Application of High-Dimensional Iterative Causal Forest to Identify Subgroups.

Pharmacoepidemiology and drug safety
BACKGROUND: Glucagon-like Peptide-1 Receptor Agonists (GLP1RA) may reduce asthma exacerbation (AE) risk, but it is unclear which populations benefit most. Recent pharmacoepidemiologic studies have employed iterative causal forest (iCF), a machine lea...

A robust machine learning model based on ribosomal-subunit-derived piRNAs for diagnostic potential of nonsmall cell lung cancer across multicentre, large-scale of sequencing data.

Clinical and translational medicine
Nonsmall cell lung cancer (NSCLC) is a lethal cancer and lacks robust biomarkers for noninvasive clinical diagnosis. Detecting NSCLC at the early stage can decrease the mortality rate and minimise harm caused by various treatments. We curated 2050 sa...

Risk Stratification of Dengue Cases Requiring Hospitalization.

Journal of medical virology
Dengue pathogenesis involves immune-driven inflammation that contributes to severe disease progression. This study assessed a machine learning model to identify a minimal, yet highly predictive biomarker set, aiming to support clinical decision-makin...

Comprehensive Prediction of the Relative Modulus of Strut-Based Gyroid Lattice Structures Employing an ML-Based Surrogate Model.

Journal of biomedical materials research. Part B, Applied biomaterials
Due to its porous structure, tunable properties, and nearly isotropic characteristics, the Gyroid Lattice Structure (GLS) is widely utilized in orthopedic implant applications. To effectively reduce stress shielding and enhance implant longevity, it ...

Investigating the determinants of performance in machine learning for protein fitness prediction.

Protein science : a publication of the Protein Society
Machine learning (ML) has revolutionized protein biology, solving long-standing problems in protein folding, scaffold generation, and function design tasks. A range of architectures have shown success on supervised protein fitness prediction tasks. N...

PSR-MAPMS: A new approach for the interpretable prediction of myelin autoantigenic peptides in multiple sclerosis using multi-source propensity scores.

Protein science : a publication of the Protein Society
Within the central nervous system, the myelin sheath is composed of elements known as myelin autoantigens that are mistakenly targeted by the immune system in multiple sclerosis (MS). This autoimmune attack leads to the destruction of myelin, resulti...