AIMC Topic: Machine Learning
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Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.
Scientific reports
Jun 4, 2025
Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and early prediction of sAKI has an important role in timely intervention, ultimately improving the patients...
Identification of key proteins and pathways in myocardial infarction using machine learning approaches.
Scientific reports
Jun 4, 2025
Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for improved diagnosis and treatment. This study combines proteomics, transcriptomics and machine learning...
Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.
Scientific reports
Jun 4, 2025
Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcomes. Our study aimed to assess the predictive risk factors for UR, to develop and validate an easy-to-...
Predicting breast self-examination awareness in Sub-Saharan Africa using machine learning.
Scientific reports
Jun 4, 2025
Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of healthcare practitioners, transportation to health facilities, and other indirect costs. Furthermore, it...
Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models.
Scientific reports
Jun 4, 2025
For analysis of crystallization, the solubility of drug in solvents should be correlated to input parameters. In this investigation, the solubility of salicylic acid as drug model in a variety of solvents is predicted through the utilization of multi...
Optimal graph representations and neural networks for multichannel time series data in seizure phase classification.
Scientific reports
Jun 4, 2025
In recent years, several machine-learning (ML) solutions have been proposed to solve the problems of seizure detection, seizure phase classification, seizure prediction, and seizure onset zone (SOZ) localization, achieving excellent performance with ...
Artificial intelligence enhanced electrochemical immunoassay for staphylococcal enterotoxin B.
Scientific reports
Jun 4, 2025
Staphylococcal enterotoxin B (SEB) holds critical importance in disease diagnosis, food safety, and public health due to its high toxicity and potent pathogenicity. Traditional immunoassay methods for detecting SEB often exhibit insufficient accuracy...
Powdery mildew resistance prediction in Barley (Hordeum Vulgare L) with emphasis on machine learning approaches.
Scientific reports
Jun 4, 2025
By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley (Hordeum Vulgare L). A 130-line F8-F9 barley population caused Badia and Kavir to grow at the Gonbad K...
Mortality Prediction Performance Under Geographical, Temporal, and COVID-19 Pandemic Dataset Shift: External Validation of the Global Open-Source Severity of Illness Score Model.
Critical care explorations
Jun 4, 2025
BACKGROUND: Risk-prediction models are widely used for quality of care evaluations, resource management, and patient stratification in research. While established models have long been used for risk prediction, healthcare has evolved significantly, a...
A comparative study of various statistical and machine learning models for predicting restaurant demand in Bangladesh.
PloS one
Jun 4, 2025
Precise demand forecasting has become crucial for merchants due to the growing complexity of client behavior and market dynamics. This allows them to enhance inventory management, minimize instances of stock outs, and enhance overall operational effi...
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