Latest AI and machine learning research in intensivists for healthcare professionals.
One of the major threats to marine ecosystems is pollution, particularly, that associated with the o...
The segmentation of the left ventricle endocardium (LV) and the left ventricle epicardium (LV) in ec...
Chronic obstructive pulmonary disease (COPD) concerns the serious decline of human lung functions. T...
BACKGROUND AND OBJECTIVE: Integrating multi-omics data for the comprehensive analysis of the biologi...
BACKGROUND: Chest radiographs are routinely performed in intensive care unit (ICU) to confirm the co...
Machine learning method has become a popular, convenient and efficient computing tool applied to man...
Accurate prediction of postoperative complications can inform shared decisions regarding prognosis, ...
OBJECTIVES: To evaluate the accuracy of a bedside, real-time deployment of a deep learning (DL) mode...
Due to the high occupational pressure suffered by intensive care units (ICUs), a correct estimation ...
BACKGROUND: Intensive Care Unit (ICU) readmissions represent both a health risk for patients,with in...
In the medical field, various clinical information has been accumulated to help clinicians provide p...
With the rapid development of artificial intelligence and image processing technology, medical imagi...
Advances in instrumentation and technique have facilitated minimally invasive surgeries for cardiac ...
Neural network (NN) has been tentatively combined into multi-objective genetic algorithms (MOGAs) to...
Synergistic drug combinations have demonstrated effective therapeutic effects in cancer treatment. D...
We present our novel deep multi-task learning method for medical image segmentation. Existing multi-...
The cardiopulmonary exercise test (CPET) constitutes a gold standard for the assessment of an indivi...
This paper proposes a two phases-based training method to design the codewords to map the cluster in...
This paper addresses the problem of multi-robot task scheduling in Antarctic environments. There are...
Over the past years, convolutional neural networks based methods have dominated the field of medical...
In recent years, human activity recognition (HAR) technologies in e-health have triggered broad inte...