AIMC Topic: Machine Learning

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MONTUR project: Dataset for understanding and forecasting tourist flows.

PloS one
This study presents an advanced system for monitoring and forecasting tourist flows in the Aosta Valley using distributed sensor technologies, cameras, and machine learning algorithms. This innovative system is designed to provide real-time data on a...

Use of machine learning for early prediction of short-term mortality in veterans with metabolic dysfunction-associated steatotic liver disease.

PloS one
BACKGROUND: Metabolic dysfunction associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide and affects >25% in the United States population. We hypothesized that clinical features present in electronic health r...

Leveraging spatial data infrastructure for machine learning based building energy performance prediction.

PloS one
The calculation, management and maintenance of energy performance of buildings (EPBs) are significant in increasing energy efficiency in buildings and reducing greenhouse gas emissions since it is estimated that approximately one third of energy cons...

Comparison of serum lactate and lactate-derived ratios as prognostic biomarkers in pediatric dengue shock syndrome using supervised machine learning models.

PloS one
BACKGROUND: Dengue shock syndrome (DSS), with critical complications encompassing mechanical ventilation (MV), dengue-associated acute liver failure (PALF), and encephalitis, is associated with high mortality in children. Although serum lactate is a ...

Machine learning reveals distinct T-cell receptor clusters in plasma cell dyscrasias compared to healthy controls.

PloS one
T-cell receptor (TCR) repertoire diversity has been implicated in the progression and prognosis of multiple myeloma (MM). This study aimed to evaluate the association between T-cell clonality, immune response, and clinical outcomes in patients with p...

Revolutionizing cervical cancer care: the synergistic effects of hyperthermia and machine learning.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
OBJECTIVE: This study aimed to examine the impact of hyperthermia in conjunction with concurrent chemoradiotherapy (CCRT) on peripheral immune markers in patients with locally advanced cervical cancer (LACC). Additionally, we sought to predict the as...

T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy.

Food chemistry
Bread loaf volume is a critical indicator of wheat processing quality, but conventional bread-making tests are laborious and time-consuming. This study evaluated near-infrared spectroscopy combined with machine learning for rapid prediction of loaf v...

Development of an explainable machine learning asthma prediction model using serum brominated flame retardants in a national population.

Clinical and experimental medicine
We aimed to explore the association of serum brominated flame retardant (BFR) metabolites and mixture profiles with asthma risk among US adults. Data were sourced from the National Health and Nutrition Examination Survey (NHANES), 1999-2023. Four mac...

Development of a machine learning-based prediction model for acute kidney injury associated with respiratory failure in the intensive care unit.

Clinical and experimental medicine
Acute kidney injury (AKI) is a frequent and severe complication in intensive care unit (ICU) patients with respiratory failure, associated with high mortality, prolonged hospitalization, and substantial healthcare burden. Conventional risk scores, su...

Hybrid Sampling and Ensemble Learning for Food Safety Sampling Inspection Classification.

Journal of food protection
Food safety sampling inspection is critical for risk prevention in complex supply chains. However, extreme class imbalance, where unqualified samples are significantly outnumbered by qualified ones, biases machine learning (ML) models to prioritize m...