AIMC Topic: Algorithms

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Interpretable machine learning model for predicting clinically significant prostate cancer: integrating intratumoral and peritumoral radiomics with clinical and metabolic features.

BMC medical imaging
BACKGROUND: To develop and validate an interpretable machine learning model based on intratumoral and peritumoral radiomics combined with clinicoradiological features and metabolic information from magnetic resonance spectroscopy (MRS), to predict cl...

A robust Parkinson's disease detection model based on time-varying synaptic efficacy function in spiking neural network.

BMC neurology
Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the world. Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high e...

Quantum-resilient software security: A fuzzy AHP-based assessment framework in the era of quantum computing.

PloS one
The introduction of quantum computing has transformed the setting of information technology, bringing both unprecedented opportunities and significant challenges. As quantum technologies continue to evolve, addressing their implications for software ...

Risk factors and predictive model construction for lower extremity arterial disease in diabetic patients.

PloS one
OBJECTIVE: To understand the prevalence and associated risk factors of lower extremity arterial disease (LEAD) in Chinese diabetic patients and to construct a risk prediction model.

Accurate localization of indoor high similarity scenes using visual slam combined with loop closure detection algorithm.

PloS one
Accurate localization is a critical technology for the application of intelligent robots and automation systems in complex indoor environments. Traditional visual SLAM (Simultaneous Localization and Mapping) techniques often face challenges with loca...

Leveraging feature extraction and risk-based clustering for advanced fault diagnosis in equipment.

PloS one
In the contemporary manufacturing landscape, the advent of artificial intelligence and big data analytics has been a game-changer in enhancing product quality. Despite these advancements, their application in diagnosing failure probability and risk r...

Fault diagnosis of nonlinear analog circuits using generalized frequency response function and LSSVM.

PloS one
A fault diagnosis method of nonlinear analog circuits is proposed that combines the generalized frequency response function (GFRF) and the simplified least squares support vector machine (LSSVM). In this study, the harmonic signal is used as an input...

Free-space optical spiking neural network.

PloS one
Neuromorphic engineering has emerged as a promising avenue for developing brain-inspired computational systems. However, conventional electronic AI-based processors often encounter challenges related to processing speed and thermal dissipation. As an...

Development and validation of machine learning algorithms for early detection of ankylosing spondylitis using magnetic resonance images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundAnkylosing spondylitis (AS) is a chronic inflammatory disease affecting the sacroiliac joints and spine, often leading to disability if not diagnosed and treated early.ObjectiveIn this study, we present the development and validation of mac...