AIMC Topic: Ecosystem

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Disrupting the infectious disease ecosystem in the digital precision health era innovations and converging emerging technologies.

Antimicrobial agents and chemotherapy
This commentary explores the convergence of precision health and evolving technologies, including the critical role of artificial intelligence (AI) and emerging technologies in infectious diseases (ID) and microbiology. We discuss their disruptive im...

New deep learning-based methods for visualizing ecosystem properties using environmental DNA metabarcoding data.

Molecular ecology resources
Environmental DNA (eDNA) metabarcoding provides an efficient approach for documenting biodiversity patterns in marine and terrestrial ecosystems. The complexity of these data prevents current methods from extracting and analyzing all the relevant eco...

A synergistic future for AI and ecology.

Proceedings of the National Academy of Sciences of the United States of America
Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in comp...

Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.

Sensors (Basel, Switzerland)
The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchai...

Comprehensive study of algal blooms variation in Jiaozhou Bay based on google earth engine and deep learning.

Scientific reports
The Jiaozhou Bay ecosystem, a crucial marine ecosystem in China, has been plagued by frequent harmful algal blooms as due to deteriorating water quality and eutrophication. This study analyzed the temporal and spatial changes of harmful algal blooms ...

Current status and practical considerations of artificial intelligence use in screening and diagnosing retinal diseases: Vision Academy retinal expert consensus.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The application of artificial intelligence (AI) technologies in screening and diagnosing retinal diseases may play an important role in telemedicine and has potential to shape modern healthcare ecosystems, including within ophthalm...

CRISPR-Cas-Based Biomonitoring for Marine Environments: Toward CRISPR RNA Design Optimization Via Deep Learning.

The CRISPR journal
Almost all of Earth's oceans are now impacted by multiple anthropogenic stressors, including the spread of nonindigenous species, harmful algal blooms, and pathogens. Early detection is critical to manage these stressors effectively and to protect ma...

Environmental vulnerability evolution in the Brazilian Amazon.

Anais da Academia Brasileira de Ciencias
Decision making and environmental policies are mainly based on propensity level to impact in the area. The propensity level can be determined through artificial intelligence techniques included in geotechnological universe. Thus, this study aimed to ...

Deep learning-based classification of microalgae using light and scanning electron microscopy images.

Micron (Oxford, England : 1993)
Microalgae possess diverse applications, such as food production, animal feed, cosmetics, plastics manufacturing, and renewable energy sources. However, uncontrolled proliferation, known as algal bloom, can detrimentally impact ecosystems. Therefore,...

Population-Based Applications and Analytics Using Patient-Reported Outcome Measures.

The Journal of the American Academy of Orthopaedic Surgeons
The intersection of big data and artificial intelligence (AI) has resulted in advances in numerous areas, including machine learning, computer vision, and natural language processing. Although there are many potentially transformative applications of...