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{bio,medical} informatics

Thursday, June 20, 2002

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find related articles. powered by google. Science Daily Gene Expression Profiles Predict Survival Of Lymphoma Patients After Chemotherpy

"Patterns of genes that are active in tumor cells can predict whether patients with diffuse large B-cell lymphoma (DLBCL) are likely to be cured by chemotherapy, scientists reported today in the New England Journal of Medicine. Researchers analyzed thousands of genes in lymphoma biopsy samples from patients with DLBCL and determined that the activity of as few as 17 genes could be used to predict patients' response to treatment. "We're able to reliably predict the survival of these patients using data from a small number of genes, indicating that this technique should be entirely manageable for routine use," said National Cancer Institute (NCI) investigator Louis M. Staudt, M.D, Ph.D., the senior author on the study."

redux [05.31.01]
find related articles. powered by google. Wired News Fingering Cancer Genes

"Genes have fingerprints just like fingers, which got one cancer researcher thinking.

Since the FBI uses neural networks -- a type of artificial intelligence built to imitate neuron function in the brain -- to sift through masses of computerized fingerprint data to solve crimes, why not do the same for genetic fingerprint data?"

""We trained (the neural networks) to recognize this is one cancer and this is another and this is not a cancer," Kahn said. "Eventually it learned to recognize particular features that were particular for cancer.""

find related articles. powered by google. Family Physicians' Electronic Network Diagnostic Algorithms: results at last!

"We seem to forget, sometimes, that the first researchers in AI that chosen medicine as a problem domain did so, not because of an interest in medicine, but because of an interest in diagnosis as an example of intelligent behavior. Medical diagnosis was one example (perhaps a poor one given that there are much simpler and easier models in other physical systems). Automated diagnosis has rarely interested the medical community, not because of a fear of removing the human element (we've already done that with our reimbursement system) or of replacing humans with machines but, more simply, because diagnosis (as most people view it), is not really the problem. Most clinicians manage some form of diagnosis and most patients are treated appropriately. What is needed is better information on the utility of information and the means to obtain it which least stresses the system."

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Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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