Machine Learning Models in Sepsis Outcome Prediction for ICU Patients: Integrating Routine Laboratory Tests-A Systematic Review.

Sepsis presents significant diagnostic and prognostic challenges, and traditional scoring systems, such as SOFA and APACHE, show limitations in predictive accuracy. Machine learning (ML)-based predictive survival models can support risk assessment and treatment decision-making in the intensive care unit (ICU) by accounting for the numerous and complex factors that influence the outcome in the septic patient. A systematic literature review of studies published from 2014 to 2024 was conducted using the PubMed database.

Breast Cancer Prognosis: A Study on Mortality Indicators.

The prognosis of breast cancer patients is critical for tailored treatment options. While previous observational studies have identified various prognostic markers, a consensus in their clinical application is lacking. This single-center retrospective study aimed to validate the most frequent risk factors associated with increased mortality in breast cancer patients.

Gastro-Intestinal Bleeding in COVID-19 Patients - Is There Any Causal Relation?

The novel Severe Acute Respiratory Syndrome Coronavirus-2 has put an enormous pressure on health systems around the world. The large number of severe cases that had symptoms seemingly unrelated to the respiratory system, continues to create confusion. The digestive tract is not spared either.