Centroid Regression for Preoperative Risk Assessment of Acute Type A Aortic Dissection Based on Multivariate Clinical Data. [PDF]
J Clin MedXiong Y +6 more
europepmc +1 more source
Accurate diagnosis of hemoglobinopathies with machine learning based on high-throughput proteomics. [PDF]
HemasphereWei S +9 more
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MENDELSEEK: An algorithm that predicts mendelian genes and elucidates what makes them special. [PDF]
PLoS Comput BiolZhou H, Edelman B, Skolnick J.
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GRACE-PSO: Particle Swarm Optimization with Group Rank Assessment and Cooperative Evolution. [PDF]
Biomimetics (Basel)Wu H, Li J, Zhang Y, Gu L, Wang P.
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Bio-Inspired Metaheuristic Optimization of a DWT-BiLSTM Architecture for Wind Speed Forecasting: A Statistical Benchmark with Component Ablation. [PDF]
Biomimetics (Basel)Bendeş E.
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Integrating Mind Mapping with Virtual Simulation: A Cognitive Scaffolding for Clinical Reasoning in Residency. [PDF]
Int J Womens HealthChen Q, Xi F, Lv M.
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The Picard–Mann Iteration With s-Convexity in the Generation of Mandelbrot and Julia Sets [PDF]
Monatshefte Fur Mathematik, 2021 In recent years, researchers have studied the use of different iteration processes from fixed point theory in the generation of complex fractals. For instance, the Mann, Ishikawa, Noor, Jungck–Mann and Jungck–Ishikawa iterations have been used.
Krzysztof Gdawiec +2 more
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On the Convergence Rate of the Krasnosel’skiĭ–Mann Iteration [PDF]
Bulletin of the Australian Mathematical Society, 2017 The Krasnosel’skiĭ–Mann (KM) iteration is a widely used method to solve fixed point problems. This paper investigates the convergence rate for the KM iteration. We first establish a new convergence rate for the KM iteration which improves the known big-$O$ rate to little-$o$ without any other restrictions. The proof relies on the connection between the
Shin-Ya Matsushita
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