A computational method that combines clinicodemographic variables with deep learning of pre-treatment histology images could predict response to immune checkpoint blockade among patients with advanced melanoma, according ...
Nov 18, 2020
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Researchers from Sechenov University together with colleagues from several Russian institutes analysed data on the RNA structure of tick-borne encephalitis virus. Much larger than in previous studies, the data volume of the ...
May 21, 2020
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Researchers at the Johns Hopkins Kimmel Cancer Center used machine learning techniques to detect mutational signatures in cancer patients. Their algorithm outperformed the current standard of analysis and revealed new mutational ...
Mar 30, 2021
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Anxiety and depression are serious mental health problems that a growing number of people seem to be facing. These conditions can tragically lead to suicidal thoughts and actions. As such, new research in the International ...
Mar 9, 2023
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Every day the human brain encounters a cacophony of sounds, often all simultaneously competing for its attention.
Jul 19, 2013
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Researchers at Moffitt Cancer Center and colleagues at the Mayo Clinic in Rochester, Minn., have developed a novel computer algorithm to easily quantify a major risk factor for breast cancer based on analysis of a screening ...
Feb 1, 2013
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Rutgers researchers can predict which patients will benefit from a popular prostate cancer drug—and they have devised a strategy that may make the treatment work longer.
Jan 22, 2024
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(Medical Xpress)—Eyewitness identification evidence is often persuasive in the courtroom and yet current eyewitness identification tests often fail to pick the culprit. Even worse, these tests sometimes result in wrongfully ...
Aug 28, 2012
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Researchers at Columbia University Medical Center (CUMC) have developed a computer algorithm that is helping scientists see how drugs produce pharmacological effects inside the body. The study, published in the journal Cell, ...
Jul 23, 2015
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(HealthDay)—A novel scoring system and algorithm can be used to classify eosinophilic chronic rhinosinusitis (ECRS) by disease severity, according to a study published online May 6 in Allergy.
May 21, 2015
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