AIMC Topic: Machine Learning
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Computational Material Science Has a Data Problem.
Journal of chemical information and modeling
Jun 4, 2025
We present an overdue questioning of the computational material science data: Is it suitable for training machine learning models? By examining the energy above the convex hull (), the electronic bandgap, and the formation energy data in the Material...
Prediction of Metal Nanoparticle Interactions with Soil Properties: Machine Learning Insights into Soil Health Dynamics.
ACS nano
Jun 4, 2025
Metal nanoparticles (MNPs) offer great potential to enable precision and sustainable agriculture. However, a comprehensive understanding of the interactions between multiple MNPs and soil properties, including impacts on overall soil health, remains ...
Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning.
Environmental science & technology
Jun 4, 2025
Understanding aerosol vertical distribution is crucial for aerosol pollution mitigation but is hindered by limited observational data. This study employed multiaxis differential optical absorption spectroscopy (MAX-DOAS) technology with a coupled rad...
Shining Light on DNA Mutations through Machine Learning-Augmented Vibrational Spectroscopy.
Analytical chemistry
Jun 4, 2025
A method to directly predict the number of nucleic acid bases in a single-stranded DNA (ssDNA) or a genomic DNA has been proposed with a combination of Raman spectroscopy and an Artificial Neural Network (ANN) algorithm. In this work, the algorithm w...
Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.
Science advances
Jun 4, 2025
Despite advances in machine learning and computer vision for biomedical imaging, machine reading and learning of colors remain underexplored. Color consistency in computer vision, color constancy in human perception, and color accuracy in biomedical ...
Prediction of depression risk in middle-aged and elderly Cardiovascular-Kidney-Metabolic syndrome patients by social and environmental determinants of health: an interpretable machine learning approach using longitudinal data from China.
Journal of health, population, and nutrition
Jun 4, 2025
BACKGROUND: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disease characterized by pathophysiological interactions between the cardiovascular system, chronic kidney disease, and metabolic risk factors. In China, the prevalence of CKM i...
Machine learning in dentistry and oral surgery: charting the course with bibliometric insights.
Head & face medicine
Jun 4, 2025
BACKGROUND: We aimed to comprehensively analyze the application of machine learning (ML) in dentistry and oral surgery using bibliometric methods to identify research trends, hotspots, and future directions.
HLN-DDI: hierarchical molecular representation learning with co-attention mechanism for drug-drug interaction prediction.
BMC bioinformatics
Jun 4, 2025
BACKGROUND: Accurate identification of drug-drug interactions (DDIs) is critical in pharmacology, as DDIs can either enhance therapeutic efficacy or trigger adverse reactions when multiple medications are administered concurrently. Traditional method...
Machine learning-based prediction of respiratory depression during sedation for liposuction.
Scientific reports
Jun 4, 2025
Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to respiratory depression. A tool that enables early detection of respiratory compromise could not only enhance patient safety during procedural sedation...
UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.
World journal of urology
Jun 4, 2025
PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcinoma (RCC) is a cornerstone of presurgical planning. We sought to create and validate U.N.I.K., a machine learning (ML) model capable of predicting beni...
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