AIMC Topic: Machine Learning

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Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care.

Critical care (London, England)
BACKGROUND AND OBJECTIVES: Excess fluid balance in acute kidney injury (AKI) may be harmful, and conversely, some patients may respond to fluid challenges. This study aimed to develop a prediction model that can be used to differentiate between volum...

A Deep-Learning Model for Subject-Independent Human Emotion Recognition Using Electrodermal Activity Sensors.

Sensors (Basel, Switzerland)
One of the main objectives of Active and Assisted Living (AAL) environments is to ensure that elderly and/or disabled people perform/live well in their immediate environments; this can be monitored by among others the recognition of emotions based on...

Using machine-learning methods to support health-care professionals in making admission decisions.

The International journal of health planning and management
BACKGROUND: Large tertiary hospitals usually face long waiting lines; patients who want to receive hospitalization need to be screened in advance. The patient admission screening process involves a health-care professional ranking patients by analyzi...

Machine learning applied to multi-sensor information to reduce false alarm rate in the ICU.

Journal of clinical monitoring and computing
Studies reveal that the false alarm rate (FAR) demonstrated by intensive care unit (ICU) vital signs monitors ranges from 0.72 to 0.99. We applied machine learning (ML) to ICU multi-sensor information to imitate a medical specialist in diagnosing pat...

Application of Deep-Learning Methods to Bird Detection Using Unmanned Aerial Vehicle Imagery.

Sensors (Basel, Switzerland)
Wild birds are monitored with the important objectives of identifying their habitats and estimating the size of their populations. Especially in the case of migratory bird, they are significantly recorded during specific periods of time to forecast a...

Accelerometer-Based Human Fall Detection Using Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Human falls are a global public health issue resulting in over 37.3 million severe injuries and 646,000 deaths yearly. Falls result in direct financial cost to health systems and indirectly to society productivity. Unsurprisingly, human fall detectio...

Use of Machine Learning in the Analysis of Indoor ELF MF Exposure in Children.

International journal of environmental research and public health
Characterization of children exposure to extremely low frequency (ELF) magnetic fields is an important issue because of the possible correlation of leukemia onset with ELF exposure. Cluster analysis-a Machine Learning approach-was applied on personal...

Heterogeneous effects of alveolar recruitment in acute respiratory distress syndrome: a machine learning reanalysis of the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial.

British journal of anaesthesia
BACKGROUND: Despite a robust physiological rationale, recruitment manoeuvres with PEEP titration were associated with harm in the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART). We sought to investigate the potential heterog...

Plaque components segmentation in carotid artery on simultaneous non-contrast angiography and intraplaque hemorrhage imaging using machine learning.

Magnetic resonance imaging
PURPOSE: This study sought to determine the feasibility of using Simultaneous Non-contrast Angiography and intraPlaque Hemorrhage (SNAP) to detect the lipid-rich/necrotic core (LRNC), and develop a machine learning based algorithm to segment plaque c...

Assisting radiologists with reporting urgent findings to referring physicians: A machine learning approach to identify cases for prompt communication.

Journal of biomedical informatics
Radiologists are expected to expediently communicate critical and unexpected findings to referring clinicians to prevent delayed diagnosis and treatment of patients. However, competing demands such as heavy workload along with lack of administrative ...