Results 141 to 150 of about 136,209 (296)

Decision Making in the Practice of Plant Disease Management

, 2007
In the practice of disease management, the challenges faced by decision makers are many and various. We outline two approaches to evidence-based decision making that have application in disease management.
Madden, L. V., Hughes, G., Van Den Bosch, F.   +2 more
core   +1 more source

A survey of multi-objective sequential decision-making

, 2013
Sequential decision-making problems with multiple objectives arise naturally in practice and pose unique challenges for research in decision-theoretic planning and learning, which has largely focused on single-objective settings.
S Whiteson (13598977), Richard Dazeley (13066251), DM Roijers (15791534), P Vamplew (13351392)   +3 more
core   +1 more source

Accelerating Probabilistic Planning Research: High-Speed Implementations of Stochastic Markov Decision Processes and Their Catalogization

IEEE Access
Probabilistic planning research, such as improvements to Monte Carlo Tree Search, is faced with two challenges. Firstly, one usually requires an algorithm’s evaluation on a variety of test problems, trying several hundred or even thousands of ...
Robin Schmocker, Alexander Dockhorn, Bodo Rosenhahn   +2 more
doaj   +1 more source

Optimal use of simplified social information in sequential decision-making. [PDF]

J R Soc Interface, 2021
Mann RP.
europepmc   +1 more source

Keratin 19 as a prognostic marker and contributing factor of metastasis and chemoresistance in high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch, Isabel Vogel, Sina Nokodian, Johanna Moeller, Antonia Blechschmidt, Vicky Hecht, Vanessa Kuentzel, Katharina Thiedig, Melissa Schwab, Oliver Schilling, Holger Bronger, Marion Kiechle, Viktor Magdolen, Tobias Dreyer   +13 more
wiley   +1 more source

Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making. [PDF]

PLoS Comput Biol, 2021
Xu HA, Modirshanechi A, Lehmann MP, Gerstner W, Herzog MH.   +4 more
europepmc   +1 more source

Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma

Molecular Oncology, EarlyView.
The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic, Anne Nørremølle, Lilian Bomme Ousager, Lars van Brakel Andersen, Marie Louise Mølgaard Binderup, Mads Thomassen   +5 more
wiley   +1 more source

Sequential Decision Making With Resource Constraints [PDF]

, 2014
In sequential decision making, an algorithm interacts with an environment, where it can learn from the feedback of its past actions. A model for sequential decision making with partial feedback is the multi-armed bandit problem. This model has also found
Badanidiyuru Varadaraja, Ashwinkumar
core  

Dual PI3K/AKT and CDK4/6 inhibition reveals selective sensitivity in an SHH medulloblastoma stem cell model

Molecular Oncology, EarlyView.
Targeted therapy was evaluated in SHH medulloblastoma using neuroepithelial stem cell (NES) and tumor‐derived NES‐like (tNES) models in 2D monolayers and 3D spheroids. PI3K, AKT, and CDK4/6 inhibitors had minimal effects in NES but markedly reduced viability and growth and induced apoptosis in tNES cells, revealing distinct therapeutic vulnerabilities.
Monika Lukoseviciute, Madeleine Birgersson, Paolo Ceriani, Margareta Wilhelm, Ourania N Kostopoulou   +4 more
wiley   +1 more source

Context-Dependent Criteria for Dirichlet Process in Sequential Decision-Making Problems

Mathematics
In models with insufficient initial information, parameter estimation can be subject to statistical uncertainty, potentially resulting in suboptimal decision-making; however, delaying implementation to gather more information can also incur costs.
Ksenia Kasianova, Mark Kelbert
doaj   +1 more source