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 ...

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 ...

Today at the San Antonio Breast Cancer Symposium (SABCS), researchers presented the initial findings from a major multi-year collaboration between the ECOG-ACRIN Cancer Research Group (ECOG-ACRIN) and ...

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 ...

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 ...

Approximately 20% to 30% of men with prostate cancer experience disease recurrence within 5 years of therapeutic intervention. 1 A key challenge in managing these patients is a scarcity of accurate ...

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 ...

Please provide your email address to receive an email when new articles are posted on . A diagnostic algorithm for classifying chronic rhinosinusitis demonstrated utility in determining refractoriness ...

Identifying Women at High Risk for Breast Cancer Using Data From the Electronic Health Record Compared With Self-Report Using publicly available translation tables along with clinician and other ...