AIMC Topic: Algorithms

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Identifying the relative importance of predictors of survival in out of hospital cardiac arrest: a machine learning study.

Scandinavian journal of trauma, resuscitation and emergency medicine
INTRODUCTION: Studies examining the factors linked to survival after out of hospital cardiac arrest (OHCA) have either aimed to describe the characteristics and outcomes of OHCA in different parts of the world, or focused on certain factors and wheth...

Toward a Common Framework and Database of Materials for Soft Robotics.

Soft robotics
To advance the field of soft robotics, a unified database of material constitutive models and experimental characterizations is of paramount importance. This will facilitate the use of finite element analysis to simulate their behavior and optimize t...

Pinning bipartite synchronization for inertial coupled delayed neural networks with signed digraph via non-reduced order method.

Neural networks : the official journal of the International Neural Network Society
The study investigates bipartite synchronization of inertial coupled delayed neural networks (ICDNNs) with signed digraph by non-reduced order method and pinning control. The second-order CDNNs will not be converted into a first-order differential sy...

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

Pharmacological research
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...

A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study.

The Lancet. Digital health
BACKGROUND: Anaemia is an important health-care burden globally, and screening for anaemia is crucial to prevent multi-organ injury, irreversible complications, and life-threatening adverse events. We aimed to establish whether a deep learning algori...

Automatic left ventricle segmentation in short-axis MRI using deep convolutional neural networks and central-line guided level set approach.

Computers in biology and medicine
In the clinical diagnosis of cardiovascular diseases, left ventricle (LV) segmentation in cardiac magnetic resonance images (MRI) is an indispensable procedure for doctors. To reduce the time needed for diagnosis, we develop an automatic LV segmentat...

Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study.

The Lancet. Digital health
BACKGROUND: Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population's general health and nutritional status. Current clinical methods of estimating fetal gestati...

A Human Support Robot for the Cleaning and Maintenance of Door Handles Using a Deep-Learning Framework.

Sensors (Basel, Switzerland)
The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door ...

Unsupervised machine learning reveals risk stratifying glioblastoma tumor cells.

eLife
A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to generate new therapeutic and biomarker hypotheses. We introduce a machine learning algorithm, Risk Assessment Population IDentification (RAPID), that is uns...