AIMC Topic: Algorithms

Clear Filters Showing 8481 to 8490 of 28713 articles

Toward the novel AI tasks in infection biology.

mSphere
Machine learning and artificial intelligence (AI) are becoming more common in infection biology laboratories around the world. Yet, as they gain traction in research, novel frontiers arise. Novel artificial intelligence algorithms are capable of addr...

Combining simulation models and machine learning in healthcare management: strategies and applications.

Progress in biomedical engineering (Bristol, England)
Simulation models and artificial intelligence (AI) are largely used to address healthcare and biomedical engineering problems. Both approaches showed promising results in the analysis and optimization of healthcare processes. Therefore, the combinati...

NeoSLAM: Long-Term SLAM Using Computational Models of the Brain.

Sensors (Basel, Switzerland)
Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics, enabling autonomous robots to navigate and create maps of unknown environments. Nevertheless, the SLAM methods that use cameras face problems in maintaini...

Automated detection of fatal cerebral haemorrhage in postmortem CT data.

International journal of legal medicine
During the last years, the detection of different causes of death based on postmortem imaging findings became more and more relevant. Especially postmortem computed tomography (PMCT) as a non-invasive, relatively cheap, and fast technique is progress...

Artificial intelligence-based prediction of the rheological properties of hydrocolloids for plant-based meat analogues.

Journal of the science of food and agriculture
BACKGROUND: Methylcellulose has been applied as a primary binding agent to control the quality attributes of plant-based meat analogues. H owever, a great deal of effort has been made to search for hydrocolloids to replace methylcellulose because of ...

Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance.

Journal of imaging informatics in medicine
This study aimed to assess the performance of a deep learning algorithm in helping radiologist achieve improved efficiency and accuracy in chest radiograph diagnosis. We adopted a deep learning algorithm to concurrently detect the presence of normal ...

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches.

Journal of applied toxicology : JAT
The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicology, there is a growing emphasis on refining, reducing, and replacing animal testing in safety evalu...

ASD-Net: a novel U-Net based asymmetric spatial-channel convolution network for precise kidney and kidney tumor image segmentation.

Medical & biological engineering & computing
Early intervention in tumors can greatly improve human survival rates. With the development of deep learning technology, automatic image segmentation has taken a prominent role in the field of medical image analysis. Manually segmenting kidneys on CT...

One-step Bayesian example-dependent cost classification: The OsC-MLP method.

Neural networks : the official journal of the International Neural Network Society
Example-dependent cost classification problems are those where the decision costs depend not only on the true and the attributed classes but also on the sample features. Discriminative algorithms that carry out such classification tasks must take thi...

An artificial intelligence algorithm for co-clustering to help in pharmacovigilance before and during the COVID-19 pandemic.

British journal of clinical pharmacology
AIMS: Monitoring drug safety in real-world settings is the primary aim of pharmacovigilance. Frequent adverse drug reactions (ADRs) are usually identified during drug development. Rare ones are mostly characterized through post-marketing scrutiny, in...