AIMC Topic: Algorithms

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Machine learning for better prediction of seepage flow through embankment dams: Gaussian process regression versus SVR and RVM.

Environmental science and pollution research international
In the present study, three machine learning methods were applied for predicting seepage flow through embankment dams, namely (i) support vector regression (SVR), relevance vector machine (RVM), and Gaussian process regression (GPR). The three models...

Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application.

Physics in medicine and biology
. In PET/CT imaging, CT is used for positron emission tomography (PET) attenuation correction (AC). CT artifacts or misalignment between PET and CT can cause AC artifacts and quantification errors in PET. Simultaneous reconstruction (MLAA) of PET act...

Hybridizing five neural-metaheuristic paradigms to predict the pillar stress in bord and pillar method.

Frontiers in public health
Pillar stability is an important condition for safe work in room-and-pillar mines. The instability of pillars will lead to large-scale collapse hazards, and the accurate estimation of induced stresses at different positions in the pillar is helpful f...

Major evolutionary transitions in individuality between humans and AI.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
That humans might undergo future evolutionary transitions in individuality (ETIs) seems fanciful. However, drawing upon recent thinking concerning the origins of properties that underpin ETIs, I argue that certain ETIs are imminently realizable. Cent...

CARES: A Corpus for classification of Spanish Radiological reports.

Computers in biology and medicine
This paper presents a new corpus of radiology medical reports written in Spanish and labeled with ICD-10. CARES (Corpus of Anonymised Radiological Evidences in Spanish) is a high-quality corpus manually labeled and reviewed by radiologists that is fr...

An artificial intelligence model for the pathological diagnosis of invasion depth and histologic grade in bladder cancer.

Journal of translational medicine
BACKGROUND: Accurate pathological diagnosis of invasion depth and histologic grade is key for clinical management in patients with bladder cancer (BCa), but it is labour-intensive, experience-dependent and subject to interobserver variability. Here, ...

A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge.

Scientific reports
Discovering a meaningful symbolic expression that explains experimental data is a fundamental challenge in many scientific fields. We present a novel, open-source computational framework called Scientist-Machine Equation Detector (SciMED), which inte...

Cross-convolutional transformer for automated multi-organs segmentation in a variety of medical images.

Physics in medicine and biology
It is a huge challenge for multi-organs segmentation in various medical images based on a consistent algorithm with the development of deep learning methods. We therefore develop a deep learning method based on cross-convolutional transformer for the...

A Neural Learning Approach for a Data-Driven Nonlinear Error Correction Model.

Computational intelligence and neuroscience
A nonlinear error correction model (ECM) is developed to fit nonlinear relationships between the nonstationary time series in a cointegration relationship. Different from the previous parametric methods, this paper constructs a hybrid neural network ...

Evaluations on supervised learning methods in the calibration of seven-hole pressure probes.

PloS one
Machine learning method has become a popular, convenient and efficient computing tool applied to many industries at present. Multi-hole pressure probe is an important technique widely used in flow vector measurement. It is a new attempt to integrate ...