Using publicly available translation tables along with clinician and other expertise, we updated the algorithms to include ICD10 codes as additional input variables. We evaluated the performance of ...
A diagnostic algorithm for classifying chronic rhinosinusitis demonstrated utility in determining refractoriness and recurrence risk for the condition, according to recent findings. Shigeharu Fujieda, ...
Researchers have proposed a machine-learning algorithm for personalized treatment selection in patients with recurrent hepatocellular carcinoma, based on data published in JAMA Surgery. “Several ...
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]), ...
Using billing or treatment codes to select patients with recurrent cancer can be misleading for researchers hoping to study the effectiveness of treatments, according to a study published recently in ...
Mayo Clinic researchers in Phoenix used artificial intelligence to create an algorithm to better predict colorectal cancer recurrence, according to a multinational study published in Gastroenterology.
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 ...
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