AIMC Topic: Algorithms

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Self-organising maps for the exploration and classification of thin-layer chromatograms.

Talanta
Thin-layer chromatography (TLC) allows the swift analysis of larger sample sets in almost any laboratory. The obtained chromatograms are patterns of coloured zones that are conveniently evaluated and classified by visual inspection. This manual appro...

Developing machine learning models for relative humidity prediction in air-based energy systems and environmental management applications.

Journal of environmental management
The prediction of relative humidity is a challenging task because of its nonlinear nature. The machine learning-based prediction strategies have attained significant attention in tackling a broad class of challenging nonlinear and complex problems. T...

A comprehensive scoping review of Bayesian networks in healthcare: Past, present and future.

Artificial intelligence in medicine
No comprehensive review of Bayesian networks (BNs) in healthcare has been published in the past, making it difficult to organize the research contributions in the present and identify challenges and neglected areas that need to be addressed in the fu...

Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for detecting, characterizing and monitoring brain tumors but definitive di...

Predicting sex from retinal fundus photographs using automated deep learning.

Scientific reports
Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. Herein we present the development of a deep learning model by clinicians without coding, which predicts reporte...

Current and emerging artificial intelligence applications for pediatric interventional radiology.

Pediatric radiology
Artificial intelligence in medicine can help improve the accuracy and efficiency of diagnostics, selection of therapies and prediction of outcomes. Machine learning describes a subset of artificial intelligence that utilizes algorithms that can learn...

Design publicity of black box algorithms: a support to the epistemic and ethical justifications of medical AI systems.

Journal of medical ethics
In their article 'Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI', Durán and Jongsma discuss the epistemic and ethical challenges raised by black box algorithms in medical practice. The opacity ...

A theory of capacity and sparse neural encoding.

Neural networks : the official journal of the International Neural Network Society
Motivated by biological considerations, we study sparse neural maps from an input layer to a target layer with sparse activity, and specifically the problem of storing K input-target associations (x,y), or memories, when the target vectors y are spar...