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 ...

Predictions for identifying 1-year seizure recurrence performed significantly better in electroencephalography (EEG) without interictal epileptiform discharges. An automated processing algorithm ...

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 ...

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 ...

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 ...

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 ...

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.

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.