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1 didate mechanism linking histone modifications to hESC fate decision.
2 nction and reward function, can be converted on-line into a decision.
4 gnal in humans that encodes the relative value of competing decision alternatives and strongly predicts behavioral value
5 nt versus deferred DAA treatment using a cost-effectiveness decision analysis model to estimate incremental cost-effectiv
6 es, integrates external signals and exerts control over the decision between self-renewal and differentiation at the tran
7 ed in the number of draws required prior to committing to a decision, but not in decision accuracy.
8 h as interpreting the visual signals so that evidence for a decision can be accumulated elsewhere.
10 ly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice rep
11 I prediction models using the machine learning algorithm of Decision Forest (DF) with Mold2 structural descriptors.
12 However, how the brain implements this important decision heuristic and what underlies individual differences
13 In many situations, a decision maker may not communicate a decision immediately and yet feel that at some point she had
14 phenomena, particularly in biology, including the cell-fate decision in developmental processes as well as the genesis an
17 of Thoracic Surgeons Predicted Risk of Mortality score for decision making and assessment of early outcome in patients e
18 Therefore, we investigated model-based versus model-free decision making and its neural correlates as well as alcohol
19 e relation between attentional mechanisms, uncertainty, and decision making and may assist the advance of approaches to p
20 suggest that PPC plays a causal role specifically in visual decision making and may support sensory aspects of the decisi
21 with relevance for cider production will allow for informed decision making for both apple producers and cider makers.
23 We first demonstrate that intertemporal decision making is prone to the attraction effect in humans.
29 The general features of this collective decision-making by a group of simple yes/no units revealed in
30 Task behavior and self-reported self-reliance for decision-making in other social contexts correlated.
31 e or the likelihood that their health information or shared decision-making preferences would be met.
32 Routine integration of FFR into the decision-making process of ACS patients with obstructive coro
33 to correct maladaptive plasticity underlying dysfunctional decision-making related to neuropsychiatric conditions.
34 ights into psychopathologies characterized by dysfunctional decision-making, such as addiction and pathological gambling.
36 uld be driven by enhanced aversion to uncertainty about the decision outcome (e.g., risk) or aversion to negative outcome
37 bjective reports correspond to the terminating process of a decision rather than a post hoc inference or arbitrary report
39 imulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics.
40 sual decision making and may support sensory aspects of the decision, such as interpreting the visual signals so that evi
41 yield after, provider overrides of evidence-based clinical decision support (CDS) for ordering computed tomographic (CT)
42 Of the 74 participants in the laboratory risky decision task (mean age, 34.2 [10.3] years), 44 (59%) were wo
45 ct graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor
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