AIMC Topic: Algorithms

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Virtual screening of drug materials for pharmaceutical tablet manufacturability with reference to sticking.

International journal of pharmaceutics Sep 16, 2024
The manufacturing of pharmaceutical solid dosage forms, such as tablets involves a large number of successive processing operations including crystallisation of the drug substance, granulation, drying, milling, mixing of the formulation, and compacti...
Powders Drug Compounding Chemistry, Pharmaceutical Excipients Machine Learning Algorithms Pharmaceutical Preparations Tablets
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Co-firing characteristic prediction of solid waste and coal for supercritical CO power cycle based on CFD simulation and machine learning algorithm.

Waste management (New York, N.Y.) Sep 16, 2024
The co-firing technology of combustible solid waste (CSW) and coal in the supercritical CO (S-CO) circulating fluidized bed (CFB) can effectively deal with domestic waste, promote social and environmental benefits, improve the coal conversion rate, a...
Machine Learning Algorithms Refuse Disposal Models, Theoretical Carbon Dioxide Air Pollutants Solid Waste Coal Power Plants
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Beyond smoothness: A general optimization framework for graph neural networks with negative Laplacian regularization.

Neural networks : the official journal of the International Neural Network Society Sep 16, 2024
Graph Neural Networks (GNNs) have drawn great attention in handling graph-structured data. To characterize the message-passing mechanism of GNNs, recent studies have established a unified framework that models the graph convolution operation as a gra...
Humans Algorithms Deep Learning Neural Networks, Computer
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GEPAF: A non-monotonic generalized activation function in neural network for improving prediction with diverse data distributions characteristics.

Neural networks : the official journal of the International Neural Network Society Sep 16, 2024
The world today has made prescriptive analytics that uses data-driven insights to guide future actions. The distribution of data, however, differs depending on the scenario, making it difficult to interpret and comprehend the data efficiently. Differ...
Neural Networks, Computer Humans Algorithms
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Joint weight optimization for partial domain adaptation via kernel statistical distance estimation.

Neural networks : the official journal of the International Neural Network Society Sep 16, 2024
The goal of Partial Domain Adaptation (PDA) is to transfer a neural network from a source domain (joint source distribution) to a distinct target domain (joint target distribution), where the source label space subsumes the target label space. To add...
Algorithms Humans Neural Networks, Computer
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A hybrid approach for modeling bicycle crash frequencies: Integrating random forest based SHAP model with random parameter negative binomial regression model.

Accident; analysis and prevention Sep 16, 2024
To effectively capture and explain complex, nonlinear relationships within bicycle crash frequency data and account for unobserved heterogeneity simultaneously, this study proposes a new hybrid framework that combines the Random Forest-based SHapley ...
London Bicycling Bayes Theorem Random Forest Accidents, Traffic Models, Statistical Regression Analysis Humans Machine Learning Algorithms Risk Factors Support Vector Machine
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Evaluation of deep learning based dose prediction in head and neck cancer patients using two different types of input contours.

Journal of applied clinical medical physics Sep 16, 2024
PURPOSE: This study evaluates deep learning (DL) based dose prediction methods in head and neck cancer (HNC) patients using two types of input contours.
Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Deep Learning Head and Neck Neoplasms Radiotherapy, Intensity-Modulated Humans Software Algorithms Prognosis
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Automated confidence estimation in deep learning auto-segmentation for brain organs at risk on MRI for radiotherapy.

Journal of applied clinical medical physics Sep 16, 2024
PURPOSE: We have built a novel AI-driven QA method called AutoConfidence (ACo), to estimate segmentation confidence on a per-voxel basis without gold standard segmentations, enabling robust, efficient review of automated segmentation (AS). We have de...
Retrospective Studies Brain Neoplasms Deep Learning Humans Algorithms Radiotherapy Dosage Radiotherapy, Intensity-Modulated Magnetic Resonance Imaging Organs at Risk Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Glioma
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A retrospective study differentiating nontuberculous mycobacterial pulmonary disease from pulmonary tuberculosis on computed tomography using radiomics and machine learning algorithms.

Annals of medicine Sep 16, 2024
OBJECTIVE: To evaluate the effectiveness of a machine learning based on computed tomography (CT) radiomics to distinguish nontuberculous mycobacterial pulmonary disease (NTM-PD) from pulmonary tuberculosis (PTB).
Humans Adult Machine Learning Radiomics Algorithms Male Retrospective Studies Tomography, X-Ray Computed Female Aged Diagnosis, Differential Middle Aged Tuberculosis, Pulmonary ROC Curve Mycobacterium Infections, Nontuberculous Support Vector Machine
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Automated classification of Alzheimer's disease, mild cognitive impairment, and cognitively normal patients using 3D convolutional neural network and radiomic features from T1-weighted brain MRI: A comparative study on detection accuracy.

Clinical imaging Sep 16, 2024
OBJECTIVES: Alzheimer's disease (AD) is a common neurodegenerative disorder that primarily affects older individuals. Due to its high incidence, an accurate and efficient stratification system could greatly aid in the clinical diagnosis and prognosis...
Aged Humans Alzheimer Disease Aged, 80 and over Neural Networks, Computer Female Male Radiomics Algorithms Reproducibility of Results Cognitive Dysfunction Brain Magnetic Resonance Imaging
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