百度试题 题目Generalizability is defined as the degree to which the validity of a selection method established in one context extends to other contexts.相关知识点: 试题来源: 解析 √ 反馈 收藏
In clinical research, this type of generalizability is also defined as conceptual reproducibility [56,57,58,59] in the literature, referring to the model’s ability to generalize and yield consistent outcomes when validating results on novel data from different sources or under various conditions. ...
where NT is the number of targets and NL is the number of ligands. A bipartite duplex network ensemble can be defined as the set of all duplexes satisfying a given set of constraints, such as the expected multidegree sequences defined in Equation (2). We determine the probability of obser...
The weighted feature map is defined as and , and the decoupling formula is defined as (6) (7) In this work, represents the rain component contained in the rain component feature map; represents the residual rain component in the background image feature map; represents the background image...
As such, deep learning approaches could provide automated solutions for such applications. However, the potential of these techniques is often undermined by challenges in reproducibility and generalizability, which are key barriers to their clinical adoption. This paper introduces the RIDGE checklist, a ...
Each DCNN model produces a probability distribution over the target data classes for each Sn and their average is defined as the vector pn = (pn(1), pn(2), pn(3), pn(4), pn(5)), where indexes 1 to 5 refer to the EDH, SDH, SAH, IVH, and IPH classes, respectively. An ...
To expand this definition: a variable X is a direct cause of a variable Y if X appears in the function that assigns Y value. Fig. 3 Reproducibility analysis presented as differences in causal node and link discovery performance (measured as F1 score) between our causal ensemble approach and ...
All models were trained using LGE CMR of MS-CMRSeg, and the root of training data is defined in data/mscmr.py as follows, root = Path('your/dataset/directory' + args.dataset) Please replace your/dataset/directory with your own directory. To train U-Net, PU-Net, Baseline, and BayeSeg...
Estimating circadian phase when sleep-wake patterns are decoupled from the endogenous circadian pacemaker, such as in most night shift workers22, is an especially challenging test of the model. We found that the model trained on ‘diurnal’ data made universally poor predictions of aMT6s acrophase...
as 0.9703 ± 0.0102, surpassing the second-best option of concatenation, 0.9845 ± 0.0147 (p = 0.001), with an improvement of 0.25% inPC. The attention map (Additional file 3: Fig. S3) clearly showed that F is the most important modality for drugs, while MC is the most...