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For instance, it has been utilized in academic research involving automatic cranio-facial implant design, [29] brain tumor analysis from Magnetic Resonance images, [30] identification of features in focal liver lesions from MRI scans, [31] radiotherapy planning for prostate cancer, [32] preparation of datasets for fluorescence microscopy ...
A number of online neuroscience databases are available which provide information regarding gene expression, neurons, macroscopic brain structure, and neurological or psychiatric disorders. Some databases contain descriptive and numerical data, some to brain function, others offer access to 'raw' imaging data, such as postmortem brain sections ...
Lung Cancer Dataset Lung cancer dataset without attribute definitions 56 features are given for each case 32 Text Classification 1992 [270] [271] Z. Hong et al. Arrhythmia Dataset Data for a group of patients, of which some have cardiac arrhythmia. 276 features for each instance. 452 Text Classification 1998 [272] [273] H. Altay et al.
However, there are relatively few databases dedicated to image collection, although some projects such as iNaturalist collect photos as a main part of their data. A special case of "images" are 3-dimensional images such as protein structures or 3D-reconstructions of anatomical structures. Image databases include, among others: [22] Allen Brain ...
Database Institute / Organization Alteration Types Primary Source [t 1] Processed Data [t 2] Organisms Cell lines [t 3] Public Data [t 4] Restricted Data [t 5]; The BioExpress® Oncology Suite from Ocimum Bio Solutions contains gene expression data from primary, metastatic, and benign tumor samples, and normal samples, including matched adjacent controls.
The most common brain tumor types in children (0–14) are: pilocytic astrocytoma, malignant glioma, medulloblastoma, neuronal and mixed neuronal-glial tumors, and ependymoma. [106] In children under 2, about 70% of brain tumors are medulloblastomas, ependymomas, and low-grade gliomas.
The Cancer Genome Atlas (TCGA) is a project to catalogue the genomic alterations responsible for cancer using genome sequencing and bioinformatics. [1] [2] The overarching goal was to apply high-throughput genome analysis techniques to improve the ability to diagnose, treat, and prevent cancer through a better understanding of the genetic basis of the disease.
Removal of tumor tissues helps decrease the pressure of the tumor on nearby parts of the brain. [17] The main goal of surgery is to remove as much as possible of the tumor mass while preserving normal brain function, and to relieve the symptoms caused by the tumor such as headache, nausea and vomiting. [ 18 ]