AIMC Topic: Machine Learning
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Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.).
Scientific reports
Aug 9, 2025
Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and M...
Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers.
Scientific reports
Aug 9, 2025
This study aimed to investigate the potential of peptide mass fingerprints (PMFs) of the serum peptidome using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in combination with machine learning algorithm...
Exploring the feasibility of AI-based analysis of histopathological variability in salivary gland tumours.
Scientific reports
Aug 9, 2025
This study uses artificial intelligence (AI) for differentiation between salivary gland tumours (SGT) using digitised Haematoxylin and Eosin stained whole-slide images (WSI). Machine learning (ML) classifiers were developed and tested using 320 scann...
Maximizing multi-source data integration and minimizing the parameters for greenhouse tomato crop water requirement prediction.
Scientific reports
Aug 9, 2025
Accurate scientific predicting of water requirements for protected agriculture crops is essential for informed irrigation management. The Penman-Monteith model, endorsed by the Food and Agriculture Organization of the United Nations (FAO), is current...
Diagnostic accuracy of machine learning approaches to identify psoriatic arthritis: a meta-analysis.
Clinical and experimental medicine
Aug 9, 2025
While machine learning (ML) approaches are commonly utilized in medical diagnostics, the accuracy of these methods in identifying psoriatic arthritis (PsA) remains uncertain. To evaluate the accuracy of ML approaches in the medical diagnosis of PsA. ...
Integrated phenotypic analysis, predictive modeling, and identification of novel trait-associated loci in a diverse Theobroma cacao collection.
BMC plant biology
Aug 9, 2025
BACKGROUND: Cacao (Theobroma cacao L.) breeding and improvement rely on understanding germplasm diversity and trait architecture. This study characterized a cacao collection (173 accessions) evaluated in Puerto Rico, examining phenotypic diversity, t...
Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.
Scientific reports
Aug 9, 2025
Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of tuberculosis preventive therapy (TPT) remains inadequately understood. Using observational data from 4152 HIV patients in Ethiopia (2005-2024), we appl...
WGCNA combined with machine learning for analysis of diagnostic markers of preeclampsia associated with the hedgehog signaling pathway.
Hypertension in pregnancy
Aug 8, 2025
BACKGROUND: Abnormal hedgehog (Hh) signaling is linked to preeclampsia (PE). This study aimed to identify Hh-related diagnostic biomarkers for PE and assess the role of immune infiltration.
Wetland dynamics in the Indus River Delta: A Sentinel-2 and machine learning approach.
Journal of environmental management
Aug 8, 2025
Coastal wetlands of the Indus River Delta are vital ecological regions that have undergone significant transformations driven by anthropogenic activities and environmental stressors. This study assesses the dynamics of wetlands and reclamation in the...
A Machine Learning-Based Modeling Approach for Dye Removal Using Modified Natural Adsorbents.
Journal of chemical information and modeling
Aug 8, 2025
This study used machine learning models to investigate the potential of biosorbents derived from natural fruit seed waste (apricot, almond, and walnut) for removing a cationic dye. Levulinic acid (LA)-modified powders of almond shell (ASh), apricot k...
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