AIMC Topic: Algorithms

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Optimised genetic algorithm-extreme learning machine approach for automatic COVID-19 detection.

PloS one
The coronavirus disease (COVID-19), is an ongoing global pandemic caused by severe acute respiratory syndrome. Chest Computed Tomography (CT) is an effective method for detecting lung illnesses, including COVID-19. However, the CT scan is expensive a...

Cellpose: a generalist algorithm for cellular segmentation.

Nature methods
Many biological applications require the segmentation of cell bodies, membranes and nuclei from microscopy images. Deep learning has enabled great progress on this problem, but current methods are specialized for images that have large training datas...

Machine-learning-driven biomarker discovery for the discrimination between allergic and irritant contact dermatitis.

Proceedings of the National Academy of Sciences of the United States of America
Contact dermatitis tremendously impacts the quality of life of suffering patients. Currently, diagnostic regimes rely on allergy testing, exposure specification, and follow-up visits; however, distinguishing the clinical phenotype of irritant and all...

Deep learning extended depth-of-field microscope for fast and slide-free histology.

Proceedings of the National Academy of Sciences of the United States of America
Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into t...

Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques.

International journal of environmental research and public health
In recent years, the widespread deployment of the Internet of Things (IoT) applications has contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies, communications and applications to maximize operational effici...

A Distributed Black-Box Adversarial Attack Based on Multi-Group Particle Swarm Optimization.

Sensors (Basel, Switzerland)
Adversarial attack techniques in deep learning have been studied extensively due to its stealthiness to human eyes and potentially dangerous consequences when applied to real-life applications. However, current attack methods in black-box settings ma...

Fully automatic wound segmentation with deep convolutional neural networks.

Scientific reports
Acute and chronic wounds have varying etiologies and are an economic burden to healthcare systems around the world. The advanced wound care market is expected to exceed $22 billion by 2024. Wound care professionals rely heavily on images and image do...

Development of a hybrid model for a partially known intracellular signaling pathway through correction term estimation and neural network modeling.

PLoS computational biology
Developing an accurate first-principle model is an important step in employing systems biology approaches to analyze an intracellular signaling pathway. However, an accurate first-principle model is difficult to be developed since it requires in-dept...

HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets.

Computational intelligence and neuroscience
In recent years, ensemble classification methods have been widely investigated in both industry and literature in the field of machine learning and artificial intelligence. The main advantage of this approach is to benefit from a set of classifiers i...

Development of a deep learning-based image eligibility verification system for detecting and filtering out ineligible fundus images: A multicentre study.

International journal of medical informatics
BACKGROUND: Recent advances in artificial intelligence (AI) have shown great promise in detecting some diseases based on medical images. Most studies developed AI diagnostic systems only using eligible images. However, in real-world settings, ineligi...