Latest AI and machine learning research in intensivists for healthcare professionals.
BACKGROUND: Current prediction models are suboptimal for determining mortality risk in patients with...
BACKGROUND: Sepsis-induced coagulopathy (SIC) is a complex condition characterized by systemic infla...
OBJECTIVES: Multi-centre, multi-vendor validation of artificial intelligence (AI) software to detect...
Automatically detecting sound events with Artificial Intelligence (AI) has become increas- ingly pop...
OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patie...
Chest X-rays are an essential diagnostic tool for identifying chest disorders because of its high s...
The detection of small molecules is critical in many fields, but traditional electrochemical detecti...
OBJECTIVE: This study aims to define the prioritisation of the needs for an intelligent robot's func...
OBJECTIVE: This study developed and validated a stacked ensemble machine learning model to predict t...
BACKGROUND: Sepsis is an organ dysfunction caused by a dysregulated host response to infection. Earl...
BACKGROUND: Agitation and sedation management is critical in intensive care as it affects patient sa...
The oviduct is the site of fertilization and preimplantation embryo development in mammals. Evidence...
BACKGROUND: Sepsis is a life-threatening disease causing millions of deaths every year. It has been ...
PURPOSE: Neonatal activity is an important physiological parameter in the neonatal intensive care un...
Accurate identification of molecular subtypes in breast cancer is critical for personalized treatmen...
Next Point-of-Interest (POI) recommendation is crucial in location-based applications, analyzing use...
Accurate staging of liver fibrosis from magnetic resonance imaging (MRI) is crucial in clinical prac...
BACKGROUND: Fusion of multi-modal data can improve the performance of deep learning models. However,...
Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating sy...
For the purpose of developing new drugs and repositioning existing ones, accurate drug-target affini...
This paper introduces a novel transfer learning framework for time series forecasting that uses Conc...