Evidence-based medicine is the most prevalent paradigm adopted by physicians. Clinical
practice guidelines typically define a set of recommendations together with eligibility criteria …

Patient similarity networks (PSNs), where patients are represented as nodes and their
similarities as weighted edges, are being increasingly used in clinical research. These …

In digital medicine, patient data typically record health events over time (eg, through
electronic health records, wearables, or other sensing technologies) and thus form unique …

Computerized clinical decision support systems can help to provide objective, standardized,
and timely dementia diagnosis. However, current computerized systems are mainly based …

Risk assessment of suicidal behavior is a time-consuming but notoriously inaccurate activity
for mental health services globally. In the last 50 years a large number of tools have been …

Aims To identify clinically meaningful clusters of patients with similar glycated hemoglobin
(HbA1c) trajectories among patients with type 2 diabetes. Methods A retrospective cohort …

Patient similarity analysis is a precondition to apply machine learning technology on medical
data. In this sense, patient similarity analysis harnesses the information wealth of electronic …

Immunotherapy is an effective way to treat non-small cell lung cancer (NSCLC). The efficacy
of immunotherapy differs from person to person and may cause side effects, making it …

Effective biomarker identification and accurate sample label prediction are still challenging
for complex diseases. Patient similarity network (PSN) analysis is a powerful tool in disease …

Cardiovascular disease is a leading cause of death among cancer survivors, second only to
cancer recurrence or development of new tumors. Cardio-oncology has therefore emerged …