AIMC Topic: Lymphoma

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Automated Diagnosis of Lymphoma with Digital Pathology Images Using Deep Learning.

Annals of clinical and laboratory science Mar 1, 2019
Recent studies have shown promising results in using Deep Learning to detect malignancy in whole slide imaging, however, they were limited to just predicting a positive or negative finding for a specific neoplasm. We attempted to use Deep Learning wi...
Neural Networks, Computer Algorithms Humans Lymphoma Automation Image Processing, Computer-Assisted Deep Learning
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GOF/LOF knowledge inference with tensor decomposition in support of high order link discovery for gene, mutation and disease.

Mathematical biosciences and engineering : MBE Feb 20, 2019
For discovery of new usage of drugs, the function type of their target genes plays an important role, and the hypothesis of "Antagonist-GOF" and "Agonist-LOF" has laid a solid foundation for supporting drug repurposing. In this research, an active ge...
Algorithms Recombinant Proteins Software Lymphoma Drug Repositioning Interleukin-2 Models, Genetic Machine Learning Humans Molecular Sequence Annotation Myelodysplastic Syndromes Interleukin-2 Receptor alpha Subunit Genetic Diseases, Inborn Genetic Variation Cost-Benefit Analysis Mutation
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Machine learning applications for the differentiation of primary central nervous system lymphoma from glioblastoma on imaging: a systematic review and meta-analysis.

Neurosurgical focus Nov 1, 2018
OBJECTIVEGlioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) are common intracranial pathologies encountered by neurosurgeons. They often may have similar radiological findings, making diagnosis difficult without surgical biopsy; h...
Central Nervous System Neoplasms Glioblastoma Neuroimaging Diagnosis, Differential Machine Learning Lymphoma Brain Neoplasms Humans
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Clinical manifestation of malignant lymphomas of the head and neck region.

Otolaryngologia polska = The Polish otolaryngology Dec 30, 2017
INTRODUCTION: Malignant lymphoma (ML) is a neoplasm caused by clonal expansion of undifferentiated B, T and NK-lymphoid cells. WHO classification divides lymphomas into two main types, i.e. Hodgkin lymphoma (HL), and non-Hodgkin lymphoma (NHL), with ...
Young Adult Poland Female Humans Aged Head and Neck Neoplasms Male Lymphoma Middle Aged Adult
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Differentiation of Glioblastoma and Lymphoma Using Feature Extraction and Support Vector Machine.

CNS & neurological disorders drug targets Jan 1, 2017
Differentiation of glioblastoma multiformes (GBMs) and lymphomas using multi-sequence magnetic resonance imaging (MRI) is an important task that is valuable for treatment planning. However, this task is a challenge because GBMs and lymphomas may have...
Lymphoma Support Vector Machine Diagnosis, Differential Magnetic Resonance Imaging Brain Humans Brain Neoplasms Sensitivity and Specificity Nonlinear Dynamics Retrospective Studies Imaging, Three-Dimensional Glioblastoma Image Interpretation, Computer-Assisted
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