This section focusses on the cutting-edge research and findings in the various disciplines of healthcare around the world.
During cardiac arrest CA and after cardiopulmonary resuscitation activation of blood coagulation and inadequate endogenous fibrinolysis occur
Atrial fibrillation AF is associated with a fivefold increased risk of stroke and a twofold increased risk of death We aimed to quantify changes in new diagnoses
Though mechanical ventilation MV is used to treat patients with severe coronavirus disease COVID little is known about the longterm health implications
Support vector machine SVM is a new machine learning method developed from statistical learning theory Since the objective function of the unconstrained
Digital contact tracing DCT applications have been introduced in many countries to aid the containment of COVID outbreaks Initially enthusiasm was high regarding their implementation as a nonpharmaceutical intervention NPI However no country was able to prevent larger outbreaks without falling back to harsher NPIs Here we discuss results of a stoch...
An electronic nose eNose device has shown a high specificity and sensitivity to diagnose or rule out tuberculosis TB in the past The aim of this study was to evaluate its performance in patients referred to INERAM Although tuberculosis TB may seem a silent pandemic compared to COVID it is responsible yearly for million cases and million notified...
Congenital heart defects are the most common type of birth defects in humans and frequently involve heart valve dysfunction The current treatment for unrepairable heart valves involves valve replacement with an implant Ross pulmonary autotransplantation or conventional orthotopic heart transplantation Although these treatments are appropriate
For a method to be widely adopted in medical research or clinical practice it needs to be reproducible so that clinicians and regulators can have confidence in its use Machine learning and deep learning have a particular set of challenges around reproducibility Small differences in the settings or the data used for training a model can lead to larg...
Data are central to research public health and in developing health information technology IT systems Nevertheless access to most data in health care is tightly controlled which may limit innovation development and efficient implementation of new research products services or systems Using synthetic data
Scar quantification on cardiovascular magnetic resonance CMR late gadolinium enhancement LGE images is important in risk stratifying patients with hypertrophic cardiomyopathy HCM due to the importance of scar burden in predicting clinical outcomes We aimed to develop a machine learning ML model that contours
