AIMC Topic: Machine Learning
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Analysis of an electrically responsive drug delivery system for ibuprofen on-demand release using a machine learning approach.
Computers in biology and medicine
Jun 20, 2025
This study aims to optimize ibuprofen-based Drug Delivery Systems (DDSs) to address their short half-life and enhance controlled release. Advanced machine learning techniques, including Artificial Neural Networks, Random Forest, and CatBoost, were em...
CPPpred-En: Ensemble framework integrating a protein language model and conventional features for highly accurate cell-penetrating peptide prediction.
Computers in biology and medicine
Jun 20, 2025
Cell-penetrating peptides (CPPs) have gained significant attention for biomedical applications, including drug delivery and therapeutic development, due to their ability to penetrate cell membranes. The accurate prediction of CPPs is critical for acc...
Decoding nutrient dynamics in coastal aquifers: Machine learning insights into submarine groundwater discharge and seawater intrusion in south India.
Chemosphere
Jun 20, 2025
Coastal aquifers are vulnerable to natural and human-induced processes that impact their resilience and ecosystems. Submarine Groundwater Discharge (SGD) and Seawater Intrusion (SWI) play crucial roles in transporting nutrients and contaminants into ...
Machine learning approaches for predicting antibiotic resistance genes abundance changes during biological nitrogen removal process.
Journal of environmental management
Jun 20, 2025
Wastewater treatment plants (WWTPs) serve as reservoirs for multiple antimicrobial agents (AAs), thereby promoting the risk of antibiotic resistance genes (ARGs) transmission in sewage and sludge during biological nitrogen removal (BNR) processes. An...
MSFCL: Drug Combination Risk Level Prediction Based on Multi-Source Feature Fusion and Contrastive Learning.
Journal of chemical information and modeling
Jun 20, 2025
Accurate assessment of drug combination risk levels is crucial for guiding rational clinical medication and avoiding adverse reactions. However, most existing methods are limited to binary classification, which fails to quantify distinctions between ...
CSU-MS: A Contrastive Learning Framework for Cross-Modal Compound Identification from MS/MS Spectra to Molecular Structures.
Analytical chemistry
Jun 20, 2025
Tandem mass spectrometry (MS/MS) is a cornerstone for compound identification in complex mixtures, but conventional spectral matching approaches face critical limitations due to limited library coverage and matching algorithms. To address this, we pr...
A machine learning model for mortality prediction in patients with severe fever with thrombocytopenia syndrome: a prospective, multicenter cohort study.
Emerging microbes & infections
Jun 19, 2025
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that imposes a considerable medical burden. In this study, we enrolled 1,606 SFTS patients, developed and validated machine learning models for mortality prediction,...
Preoperative prediction of severe short-term complications in patients with bladder cancer undergoing radical cystectomy.
Surgical oncology
Jun 19, 2025
BACKGROUND AND OBJECTIVE: Radical cystectomy (RC) is associated with a high risk of postoperative complications. The prediction of individual patient risk for severe complications can facilitate preoperative shared decision-making. Patients with elev...
Tracking the spatial and temporal evolution of salt marsh vegetation based on UAV sampling and seasonal phenology from Landsat data.
Journal of environmental management
Jun 19, 2025
Salt marshes, valued for their ecological importance, have been increasingly degraded in recent decades. Preserving salt marshes necessitates a critical approach that involves monitoring vegetation distribution and species composition. This study pre...
Development of a Machine Learning-Based Predictive Model for Postoperative Delirium in Older Adult Intensive Care Unit Patients: Retrospective Study.
Journal of medical Internet research
Jun 19, 2025
BACKGROUND: Delirium is a prevalent phenomenon among patients admitted to the geriatric intensive care unit (ICU) and can adversely impact prognosis and augment the risk of complications.
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