Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian optimization assisted unsupervised learning for efficient
  intra-tumor partitioning in MRI and survival prediction for glioblastoma
  patients   Glioblastoma is profoundly heterogeneous in microstructure and vasculature,
which may lead to tumor regional diversity and distinct treatment response.
Although successful in tumor sub-region segmentation and survival prediction,
radiomics based on machine learning algorithms, is challenged by its
robustness, due to the vague intermediate process and track changes. Also, the
weak interpretability of the model poses challenges to clinical application.
Here we proposed a machine learning framework to semi-automatically fine-tune
the clustering algorithms and quantitatively identify stable sub-regions for
reliable clinical survival prediction. Hyper-parameters are automatically
determined by the global minimum of the trained Gaussian Process (GP) surrogate
model through Bayesian optimization(BO) to alleviate the difficulty of tuning
parameters for clinical researchers. To enhance the interpretability of the
survival prediction model, we incorporated the prior knowledge of intra-tumoral
heterogeneity, by segmenting tumor sub-regions and extracting sub-regional
features. The results demonstrated that the global minimum of the trained GP
surrogate can be used as sub-optimal hyper-parameter solutions for efficient.
The sub-regions segmented based on physiological MRI can be applied to predict
patient survival, which could enhance the clinical interpretability for the
machine learning model.

10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
8
The categories of this paper are: hep-ex