Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.

Background And Objective: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive respiratory support that is used for the treatment of Acute Respiratory Distress Syndrome (ARDS), a severe medical condition diagnosed when symptoms like profound hypoxemia, pulmonary opacities on radiography, or unexplained respiratory failure are present. It can be classified as mild, moderate or severe. H-CPAP therapy is recommended as the initial treatment approach for mild ARDS.

Biologically weighted LASSO: enhancing functional interpretability in gene expression data analysis.

Motivation: Feature selection approaches are widely used in gene expression data analysis to identify the most relevant features and boost performance in regression and classification tasks. However, such algorithms solely consider each feature's quantitative contribution to the task, possibly limiting the biological interpretability of the results. Feature-related prior knowledge, such as functional annotations and pathways information, can be incorporated into feature selection algorithms to potentially improve model performance and interpretability.

Long peripheral catheters for intravenous infusions of iloprost or alprostadil therapy in rheumatologic outpatients.

Background: Long peripheral catheters (LPCs) role in Difficult IntraVenous Access (DIVA) patients admitted to the emergency department has already been studied, resulting in a rapid, safe, and cost-effective procedure. Although their use in outpatient settings is established, there is a lack of studies assessing their benefits. In particular, rheumatologic outpatients affected by scleroderma, especially those affected by digital ulcers, are often treated with intravenous infusions of prostaglandin I (PGI) analog (IV-PGIA).

Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking.

Background: High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma.