In healthcare, machine learning (ML) shows significant potential to augment patient care,
improve population health, and streamline healthcare workflows. Realizing its full potential …

The current state of Association Rule Mining (ARM) technology is heading towards a critical
yet profitable direction. The ARM process uncovers numerous association rules, determining …

Survival analysis is a fundamental tool in medicine, modeling the time until an event of
interest occurs in a population. However, in real-world applications, survival data are often …

Survival analysis, aka time-to-event analysis, has a wide-ranging impact on patient care.
Federated Survival Analysis (FSA) is an emerging Federated Learning (FL) paradigm for …

Survival analysis is a subfield of statistics concerned with modeling the occurrence time of a
particular event of interest for a population. Survival analysis found widespread applications …

Machine learning (ML) in healthcare presents numerous opportunities for enhancing patient
care, population health, and healthcare providers' workflows. However, the real-world …

The problem of executing machine learning algorithms over data while complying with data
privacy is highly relevant in many application areas, including medicine in general and …

The aim of the study was to build a machine learning-based predictive model to discriminate
between hospitalized patients at low risk and high risk of bloodstream infection (BSI). A Data …

Conducting survival analysis on distributed healthcare data is an important research
problem, as privacy laws and emerging data-sharing regulations prohibit the sharing of …

The diversity in disease profiles and therapeutic approaches between hospitals and health
professionals underscores the need for patient-centric personalized strategies in healthcare …