Researchers developed a Bayesian Gated Recurrent Unit architecture that dynamically scales trading capital using uncertainty ...
Please provide your email address to receive an email when new articles are posted on . Researchers have proposed a machine-learning algorithm for personalized treatment selection in patients with ...
The automatic rule-based recurrence detection algorithm (Auto-Recur), using notes on image reading (positron emission tomography-computed tomography [PET-CT], CT, magnetic resonance imaging [MRI]), ...
BERIL-1: Biomarker results from targeted sequencing of circulating tumor DNA (ctDNA) and archival tissue in a randomized phase II study of buparlisib (BKM120) or placebo plus paclitaxel in patients ...
Introduction Recurrent stroke remains a major threat after an index stroke, but individual risk is difficult to estimate because recurrence reflects interacting clinical, imaging, treatment, ...
Predictions for identifying 1-year seizure recurrence performed significantly better in electroencephalography (EEG) without interictal epileptiform discharges. An automated processing algorithm ...
WEST LAFAYETTE, Ind. — A Purdue University professor and several international researchers have developed a new method and algorithm that can predict the recurrence of prostate cancer in patients ...
Omitting race and ethnicity from colorectal cancer (CRC) recurrence risk prediction models could decrease their accuracy and fairness, particularly for minority groups, potentially leading to ...
Source: Getty Images A retrospective study found that a radiomic-clinicopathologic nomogram performed better than other tools in predicting biochemical recurrence-free survival after surgery for ...
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