A new machine learning framework uses single-cell transcriptomics to accurately annotate brain cell subpopulations and classify Alzheimer’s disease status.
A new explainable machine learning framework applied to South Korea’s public health insurance data reveals macroeconomic indicators associated with national ...
A district-scale study in Somalia combined satellite validation, 14 conditioning factors and ensemble machine learning to map flood susceptibility across ...
A new hybrid pipeline called SelCysML combines interpretable machine learning with BLAST-based validation to identify and functionally annotate bacterial selenoproteins ...
A stratified survey and species-distribution modelling of 47 dung beetle species in Vaud found that narrow-range species were easier to ...
A two-stage neural network fusion system from Romanian researchers achieved 93.53% F1 score in segmenting ovarian tumors from CT scans, ...
A systematic review of 200 studies finds machine learning effective for detecting DDoS and ARP spoofing attacks on university networks, ...
An ensemble species distribution model projects that the endangered African savanna elephant could lose roughly half of its climatically suitable ...
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