AIMC Topic: Machine Learning

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Machine learning framework coupled with CADD for predicting sphingosine kinase 1 inhibitors.

Computers in biology and medicine Jun 4, 2025
Sphingosine kinase 1 (SphK1) plays a pivotal role in cancer progression, metastasis, and chemotherapy resistance, making it a key target for therapeutic interventions in cancer, cardiovascular diseases, and inflammation. Machine learning models, incl...
Humans Machine Learning Enzyme Inhibitors Protein Kinase Inhibitors Phosphotransferases (Alcohol Group Acceptor) Molecular Docking Simulation Support Vector Machine Molecular Dynamics Simulation
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Machine learning-optimized bioprocess for macroidin production by Lysinibacillus macroides and its biomedical applications.

Bioprocess and biosystems engineering Jun 4, 2025
The quest for solutions to infectious diseases and life-debilitating disease states has been ongoing for centuries now. Natural products researches have revealed bioactive compounds of plant and microbial origin that offer solutions to health conditi...
Anti-Bacterial Agents Bacteriocins Bacillaceae Humans Neural Networks, Computer Machine Learning
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Predicting mortality risk following major lower extremity amputation using machine learning.

Journal of vascular surgery Jun 4, 2025
OBJECTIVE: Major lower extremity amputation for advanced vascular disease involves significant perioperative risks. Although outcome prediction tools could aid in clinical decision-making, they remain limited. To address this, we developed machine le...
Humans Machine Learning Decision Support Techniques Databases, Factual Retrospective Studies Female Postoperative Complications Time Factors Treatment Outcome Lower Extremity Risk Factors Aged Predictive Value of Tests Aged, 80 and over Amputation, Surgical Male Middle Aged Risk Assessment
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Associations between all-cause and ischemic heart disease mortality and long-term ambient ultrafine particles exposure: a comparison of statistical and machine learning exposure models.

Environment international Jun 4, 2025
BACKGROUND: Evidence about the health effects of ultrafine particles (UFPs) remains limited, especially due to challenges in estimating exposure in epidemiological studies.
Humans Machine Learning Retrospective Studies Air Pollution Particulate Matter Environmental Exposure Myocardial Ischemia Quebec Middle Aged Models, Statistical Air Pollutants Female Aged Male
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Shotgun Metagenomics Identifies in a Cross-Sectional Setting Improved Plaque Microbiome Biomarkers for Peri-Implant Diseases.

Journal of clinical periodontology Jun 4, 2025
AIM: This observational study aimed to verify and improve the predictive value of plaque microbiome of patients with dental implant for peri-implant diseases.
Peri-Implantitis Metagenomics Stomatitis Mucositis Cross-Sectional Studies Male Middle Aged Microbiota Dental Plaque Dental Implants Humans Female Aged Adult Machine Learning Biomarkers
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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...
Machine Learning Density Functional Theory Materials Science
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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 ...
Soil Microbiology Metal Nanoparticles Hydrogen-Ion Concentration Machine Learning Soil
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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...
Machine Learning China Environmental Monitoring Air Pollutants Seasons Aerosols Atmosphere
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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...
Neural Networks, Computer DNA Machine Learning Mutation DNA, Single-Stranded Algorithms Spectrum Analysis, Raman
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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 ...
Colorimetry Machine Learning Color Algorithms Humans Biological Assay Hemoglobins Image Processing, Computer-Assisted Neural Networks, Computer
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