Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association.

Artificial intelligence is poised to transform cardio-oncology by enabling personalized care for patients with cancer, who are at a heightened risk of cardiovascular disease due to both the disease and its treatments. The rising prevalence of cancer and the availability of multiple new therapeutic options has resulted in improved survival among patients with cancer and has expanded the scope of cardio-oncology to not only short-term but also long-term cardiovascular risks resulting from both cancer and its treatments. However, there is considerable heterogeneity in cardiovascular risk, driven by the nature of the malignancy as well as each individual's unique characteristics.

Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reports.

Big data can revolutionize research and quality improvement for cardiac ultrasound. Text reports are a critical part of such analyses. Cardiac ultrasound reports include structured and free text and vary across institutions, hampering attempts to mine text for useful insights.

Comparative Outcomes of Babesiosis in Immunocompromised and Non-Immunocompromised Hosts: A Multicenter Cohort Study.

Background: Babesiosis poses significant risks of adverse outcomes in individuals with immunocompromising conditions (IC) and asplenia/hyposplenia (AH). This study compares clinical outcomes between these vulnerable groups and immunocompetent patients.

Methods: A multicenter retrospective cohort study included adult patients with laboratory-confirmed babesiosis from 2009 to 2023.