AIMC Topic: Algorithms

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Deep learning-based point-scanning super-resolution imaging.

Nature methods
Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-...

Natural Language Processing and Machine Learning for Identifying Incident Stroke From Electronic Health Records: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Stroke is an important clinical outcome in cardiovascular research. However, the ascertainment of incident stroke is typically accomplished via time-consuming manual chart abstraction. Current phenotyping efforts using electronic health r...

Image-level supervised segmentation for human organs with confidence cues.

Physics in medicine and biology
Image segmentation for human organs is an important task for the diagnosis and treatment of diseases. Current deep learning-based methods are fully supervised and need pixel-level labels. Since the medical images are highly specialized and complex, t...

Sign function and ANN based pole placement for computing interval controls.

ISA transactions
This paper deals with estimation of interval controls for interval Linear Time Invariant (LTI) plants using pole placement technique. Generally, the parameters associated with LTI plant system are assumed to be crisp values, but due to the occurrence...

R-HEFS: Rough set based heterogeneous ensemble feature selection method for medical data classification.

Artificial intelligence in medicine
Feature selection is one of the trustworthy processes of dimensionality reduction technique to select a subset of relevant and non-redundant features from large datasets. Ensemble feature selection (EFS) approach is a recent technique aiming at accum...

R.ROSETTA: an interpretable machine learning framework.

BMC bioinformatics
BACKGROUND: Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a pr...

Variable Selection from Image Texture Feature for Automatic Classification of Concrete Surface Voids.

Computational intelligence and neuroscience
Machine learning plays an important role in computational intelligence and has been widely used in many engineering fields. Surface voids or bugholes frequently appearing on concrete surface after the casting process make the corresponding manual ins...

Assessment of an Artificial Intelligence Algorithm for Detection of Intracranial Hemorrhage.

World neurosurgery
BACKGROUND: Immediate and accurate detection of intracranial hemorrhages (ICHs) is essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has the potential to provide this, but the assessment of these methods need...

Deep Neural Network Approach for Continuous ECG-Based Automated External Defibrillator Shock Advisory System During Cardiopulmonary Resuscitation.

Journal of the American Heart Association
Background Because chest compressions induce artifacts in the ECG, current automated external defibrillators instruct the user to stop cardiopulmonary resuscitation (CPR) while an automated rhythm analysis is performed. It has been shown that minimiz...