PRISM classifies Acute Lymphoblastic Leukemia in blood smears by extracting features from perinuclear ring zones around nuclei, achieving 98.46% accuracy and 0.9937 precision-recall AUC without explicit cell boundary detection.
An efficient deep Convolutional Neural Network based detection and classification of Acute Lymphoblastic Leukemia
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Lattice QCD yields continuum-limit HQET LCDA parameters λ_B = 0.340(20) GeV and σ_B^(1) = 1.685(63) at 1 GeV, reducing total uncertainty by a factor of three.
A hybrid renormalization scheme removes linear divergences from baryon quasi-DAs on the lattice, producing smooth continuum distributions at multiple spacings.
citing papers explorer
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PRISM: Perinuclear Ring-based Image Segmentation Method for Acute Lymphoblastic Leukemia Classification
PRISM classifies Acute Lymphoblastic Leukemia in blood smears by extracting features from perinuclear ring zones around nuclei, achieving 98.46% accuracy and 0.9937 precision-recall AUC without explicit cell boundary detection.
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Continuum-Limit HQET LCDAs from Lattice QCD for Tightening B Decay Uncertainties
Lattice QCD yields continuum-limit HQET LCDA parameters λ_B = 0.340(20) GeV and σ_B^(1) = 1.685(63) at 1 GeV, reducing total uncertainty by a factor of three.
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Hybrid Renormalization for Baryon Distribution Amplitudes from Lattice QCD in LaMET
A hybrid renormalization scheme removes linear divergences from baryon quasi-DAs on the lattice, producing smooth continuum distributions at multiple spacings.