Results 91 to 100 of about 11,467,392 (329)
Employing active learning in the optimization of culture medium for mammalian cells
npj Systems Biology and Applications, 2023 Medium optimization is a crucial step during cell culture for biopharmaceutics and regenerative medicine; however, this step remains challenging, as both media and cells are highly complex systems.
Takamasa Hashizume +2 more
doaj +1 more source
Active Learning of Mealy Machines with Timers
We present the first algorithm for query learning Mealy machines with timers in a black-box context. Our algorithm is an extension of the L# algorithm of Vaandrager et al. to a timed setting. We rely on symbolic queries which empower us to reason on untimed executions while learning. Similarly to the algorithm for learning timed automata of Waga, these
Véronique Bruyère +4 more
openaire +6 more sources
Learning curves for decision making in supervised machine learning: a survey
Learning curves are a concept from social sciences that has been adopted in the context of machine learning to assess the performance of a learning algorithm with respect to a certain resource, e.g., the number of training examples or the number of ...
van Rijn J.N., Mohr F.
core +1 more source
FEBS Open Bio, EarlyView.The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley +1 more source
Online Active Learning in Practice [PDF]
, 2007 We compare the practical performance of several recently proposed algorithms for active learning in the online setting. We consider two algorithms (and their combined variants) that are strongly online, in that they do not store any previously labeled ...
Monteleoni, Claire, Kaariainen, Matti
core
Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA
FEBS Open Bio, EarlyView.Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley +1 more source
Active Learning for Decision-Making from Imbalanced Observational Data
, 2019 Machine learning can help personalized decision support by learning models to predict individual treatment effects (ITE). This work studies the reliability of prediction-based decision-making in a task of deciding which action a to take for a target unit
Kaski, Samuel +5 more
core +1 more source
Cell surface CD11c as a neutrophil aging marker molecule
FEBS Open Bio, EarlyView.Cell surface CD11chi neutrophils were more aged and had better phagocytic function than CD11c−/lo neutrophils. Transcriptomic analysis of CD11chi neutrophils and CD11c−/lo neutrophils in pediatric population showed that the most difference was seen in infants.
Sophia Koutsogiannaki +5 more
wiley +1 more source
Energy and AIThe physical growth of Polycyclic Aromatic Compounds (PACs) to soot particles plays a significant role in understanding the chemistry of soot formation. Insights into the process can be gained from PACs’ free energy of dimerization landscape.
Mohammed I. Radaideh +5 more
doaj +1 more source
RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu +21 more
wiley +1 more source