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How Can AI Help Improve Food Safety?

Annual review of food science and technology
With advances in artificial intelligence (AI) technologies, the development and implementation of digital food systems are becoming increasingly possible. There is tremendous interest in using different AI applications, such as machine learning model...

Design and control of soft biomimetic pangasius fish robot using fin ray effect and reinforcement learning.

Scientific reports
Soft robots provide a pathway to accurately mimic biological creatures and be integrated into their environment with minimal invasion or disruption to their ecosystem. These robots made from soft deforming materials possess structural properties and ...

Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Trustworthiness is a core tenet of medicine. The patient-physician relationship is evolving from a dyad to a broader ecosystem of health care. With the emergence of artificial intelligence (AI) in medicine, the elements of trust must be revisited. We...

Planetary Mapping Using Deep Learning: A Method to Evaluate Feature Identification Confidence Applied to Habitats in Mars-Analog Terrain.

Astrobiology
The goals of Mars exploration are evolving beyond describing environmental habitability at global and regional scales to targeting specific locations for biosignature detection, sample return, and eventual human exploration. An increase in the specif...

Knowledge Engineering in Chemistry: From Expert Systems to Agents of Creation.

Accounts of chemical research
Passing knowledge from human to human is a natural process that has continued since the beginning of humankind. Over the past few decades, we have witnessed that knowledge is no longer passed only between humans but also from humans to machines. The ...

Prediction and interpretation of antibiotic-resistance genes occurrence at recreational beaches using machine learning models.

Journal of environmental management
Antibiotic-resistant bacteria and antibiotic resistance genes (ARGs) are pollutants of worldwide concern that seriously threaten public health and ecosystems. Machine learning (ML) prediction models have been applied to predict ARGs in beach waters. ...

Novel deep learning hybrid models (CNN-GRU and DLDL-RF) for the susceptibility classification of dust sources in the Middle East: a global source.

Scientific reports
Dust storms have many negative consequences, and affect all kinds of ecosystems, as well as climate and weather conditions. Therefore, classification of dust storm sources into different susceptibility categories can help us mitigate its negative eff...

Mapping global dynamics of benchmark creation and saturation in artificial intelligence.

Nature communications
Benchmarks are crucial to measuring and steering progress in artificial intelligence (AI). However, recent studies raised concerns over the state of AI benchmarking, reporting issues such as benchmark overfitting, benchmark saturation and increasing ...

Assessment of Radiology Artificial Intelligence Software: A Validation and Evaluation Framework.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Artificial intelligence (AI) software in radiology is becoming increasingly prevalent and performance is improving rapidly with new applications for given use cases being developed continuously, oftentimes with development and validation occurring in...

Predicting ammonia nitrogen in surface water by a new attention-based deep learning hybrid model.

Environmental research
Ammonia nitrogen (NH-N) is closely related to the occurrence of cyanobacterial blooms and destruction of surface water ecosystems, and thus it is of great significance to develop predictive models for NH-N. However, traditional models cannot fully co...