Signals, in order.

The project at Inselspital Bern will develop a clinical decision support system that uses self‑learning AI to analyze cardiotocography traces from 10,000–15,000 maternity records. CSEM will design, develop, and validate multiple machine‑learning architectures to predict the optimal fetal extraction time during labor, providing a superhuman support tool for obstetricians. The system will be trained on existing clinical outcomes to improve decision‑making accuracy.

Source: ClinicalTrials.gov

Asthma is a chronic inflammatory airway disease affecting 8% of school‑aged children and 30% of preschoolers, with frequent exacerbations that are difficult for parents and patients to assess. Current assessment tools include the Pediatric Respiratory Assessment Measure (PRAM) score and lung function tests such as spirometry, but these require patient cooperation and are limited in young children. Digital stethoscopes that record and transmit auscultation data up to 20‑20,000 Hz, combined with advanced signal processing and unsupervised AI learning, offer a promising objective method to evalu…

Source: ClinicalTrials.gov

The study aims to develop a wearable-based ICU prediction algorithm for inpatients with SARS-CoV-2. Participants suspected or confirmed with COVID-19 will wear a smartwatch that collects physiological data throughout hospitalization. The collected data will be used to predict clinical trajectories.

Source: ClinicalTrials.gov

This multi-center observational case-control study in ICU patients aims to identify novel biomarkers for early recognition of severe community acquired pneumonia-associated sepsis and to predict sepsis-related mortality. Patients with sCAP will be profiled over time and compared with controls, using modern omics technologies to explore mechanisms and influencing factors. The resulting data will be analyzed with machine learning algorithms and multi-dimensional mathematical models.

Source: ClinicalTrials.gov

A prospective non‑interventional study will enroll 400 early AMD patients (600 untreated early AMD eyes) in Vienna, Austria, and follow them for at least one year. Patients will undergo Optical Coherence Tomography every four months; when the Vienna Reading Center detects focal changes, a targeted follow‑up schedule will be initiated to investigate the progression at those sites.

Source: ClinicalTrials.gov

This multi-center study in Switzerland focuses on patients with sepsis in Intensive Care Units to better understand the complex host-pathogen interaction and clinical heterogeneity associated with sepsis. The goal is to develop novel diagnostic approaches by analyzing patient data with state-of-the-art analytical algorithms, including machine learning and multidimensional mathematical modelling, within a case-control design that compares sepsis patients to controls.

Source: ClinicalTrials.gov