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- W2024951980 abstract "Researchers have programmed a computer to discriminate the pattern of gene expression of four different childhood leukemias. Neuroblastoma, rhabdomyosarcoma, non-Hodgkin lymphoma and members of the Ewing family of tumours require different therapeutic regimes for optimal treatment but are difficult to diagnose because they are very similar histologically. To tackle this problem from a new angle, a group led by Paul Meltzer from the NIH in Bethesda, USA, hybridized 63 RNA samples of the four tumour types to DNA chips [see Khan, J. et al. (Nat. Med. 7, 673–679, 2001) for the published account]. Expression profiles were fed to the so-called Artificial Neuronal Network (ANN), which is a computer-based algorithm that can be trained to recognize and categorize complex patterns. The ANN profiler filtered out specific expression patterns for all four tumour types and pinpointed the most relevant genes for the classification. Next, the new, tumour-calibrated, version of ANN accurately predicted the tumour type of 20 unknown cancers. These findings give fresh hope for improved diagnosis and prompt treatment of the four tumours. JdB" @default.
- W2024951980 created "2016-06-24" @default.
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- W2024951980 date "2001-08-01" @default.
- W2024951980 modified "2023-09-25" @default.
- W2024951980 title "Chips help diagnosis of childhood cancers" @default.
- W2024951980 doi "https://doi.org/10.1016/s0962-8924(01)02078-5" @default.
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