AIMC Topic: Algorithms

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Direct parametric reconstruction in dynamic PET using deep image prior and a novel parameter magnification strategy.

Computers in biology and medicine
BACKGROUND/PURPOSE: Multiple parametric imaging in positron emission tomography (PET) is challenging due to the noisy dynamic data and the complex mapping to kinetic parameters. Although methods like direct parametric reconstruction have been propose...

Molecular Optimization Based on a Monte Carlo Tree Search and Multiobjective Genetic Algorithm.

Journal of chemical information and modeling
In the realm of medicinal chemistry, the predominant challenge in molecular design lies in managing extensive molecular data sets and effectively screening for, as well as preserving, molecules with potential value. Traditional methodologies typicall...

Perspectives of Artificial Intelligence Use for In-House Ethics Checks of Journal Submissions.

Journal of Korean medical science
Artificial intelligence (AI) has shown its ability to transform academic writing and publishing. It offers significant benefits, including enhancing efficiency, consistency, and integrity, However, these advancements are accompanied by ethical concer...

Accuracy of Artificial Intelligence for Gatekeeping in Referrals to Specialized Care.

JAMA network open
IMPORTANCE: Integrating artificial intelligence (AI) technologies into gatekeeping holds significant potential, as it efficiently handles repetitive tasks and can process large amounts of information quickly.

Computational approaches in drug chemistry leveraging python powered QSPR study of antimalaria compounds by using artificial neural networks.

Scientific reports
The application of Machine Learning has become a revolutionary instrument in the domain of pharmaceutical research. Machine learning enables the modelling of Quantitative Structure Property Relationship, a crucial task in forecasting the physiochemic...

Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms.

PloS one
In this study, the ability of machine learning algorithms to predict tensile properties of both heat-treated and non-heat treated LPBFed AlSi10Mg alloy is investigated. The data was analyzed using various Machine Learning Regression (MLR) models such...

Early detection of occupational stress: Enhancing workplace safety with machine learning and large language models.

PloS one
Occupational stress is a major concern for employers and organizations as it compromises decision-making and overall safety of workers. Studies indicate that work-stress contributes to severe mental strain, increased accident rates, and in extreme ca...

Skin cancer segmentation and classification by implementing a hybrid FrCN-(U-NeT) technique with machine learning.

PloS one
Skin cancer is a severe and rapidly advancing condition that can be impacted by multiple factors, including alcohol and tobacco use, allergies, infections, physical activity, exposure to UV light, viral infections, and the effects of climate change. ...

Multi-view clustering via global-view graph learning.

PloS one
Multiview clustering aims to improve clustering performance by exploring multiple representations of data and has become an important research direction. Meanwhile, graph-based methods have been extensively studied and have shown promising performanc...

A hybrid PSO-FFNN approach for optimized seismic design and accurate structural response prediction in steel moment-resisting frames.

PloS one
The first steel is the most prevalent material used in building. Steel's intrinsic hardness and durability make it appropriate for different uses, but its greater adaptability makes it ideal for seismic design. The brittle fracture occurred in welded...