Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
OBJECTIVES: Traumatic intracranial hematomas represent a critical clinical situation where early detection and management are of utmost importance. Machine learning has been recently used in the detection of neuroradiological findings. Hence, it can be used in the detection of intracranial hematomas and furtherly initiate a management cascade of patient transfer, diagnostics, admission, and emerge...
Duodenal stenosis is a condition that can be related to several diseases, being either intrinsic, such as neoplasm and inflammatory stenosis, or extrinsic, such as pancreatic pseudocyst, superior mesenteric artery syndrome, and foreign bodies. Current treatments range from endoscopic approaches, such as endoscopic resection and stent placement, to surgical approaches, including duodenal resection,...
We present a pipeline in which machine learning techniques are used to automatically identify and evaluate subtypes of hospital patients admitted betw...
Robotic operations as a further development of conventional laparoscopic surgery have been introduced for nearly all interventions in visceral surgery...
In routine clinical practice, the diagnosis and treatment of cardiovascular disease (CVD) rely on data in a variety of formats. These formats comprise...
Although great progress has been made in the diagnostic and treatment options for dyslipidemias, unawareness, underdiagnosis and undertreatment of the...
Radiomics and artificial intelligence carry the promise of increased precision in oncologic imaging assessments due to the ability of harnessing thous...
Spider angiomas are dilated vascular channels in the skin. They have a central arteriole with surrounding vascular channels resembling legs of a spide...
BACKGROUND: Inflammation is a sequela of cardiovascular critical illness and a risk factor for mortality.
BACKGROUND: The accuracy of electrocardiogram (ECG) interpretation by doctors are affected by the available clinical information. However, having a co...
Nurses, often considered the backbone of global health services, are disproportionately vulnerable to COVID-19 due to their front-line roles. They con...
Applications and workflows around spinal robotics have evolved since these systems were first introduced in 2004. Initially approved for lumbar pedicl...
Dementia and mild cognitive impairment (MCI) represent significant health challenges in an aging population. As the search for noninvasive, precise an...
Pregnant women have a number of physiological changes that lower the immune responses to avoid embryonic rejection, which increases the risk of proble...
BACKGROUND: Classification of perioperative risk is important for patient care, resource allocation, and guiding shared decision-making. Using discrim...
Manual sleep staging (MSS) using polysomnography is a time-consuming task, requires significant training, and can lead to significant variability amon...
Artificial intelligence is paving the way in contemporary medical advances, with the potential to revolutionise orthopaedic surgical care. By harnessi...
After the introduction of same-day discharge (SDD) pathways for various surgeries, these pathways have demonstrated comparable complication rates and...
OBJECTIVE: This study aims to develop high-performing Machine Learning and Deep Learning models in predicting hospital length of stay (LOS) while enha...
The development of virtual care options, including virtual hospital platforms, is rapidly changing the healthcare, mostly in the pandemic period, due ...