AI Medical Compendium Topic

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Fungi

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Bioactivity and chemical screening of endophytic fungi associated with seaweeds Gracilaria sp. and Sargassum sp. of the Bay of Bengal, Bangladesh.

Scientific reports
This study explored the great potential of endophytic fungi associated with red seaweed Gracilaria sp. and brown seaweed Sargassum sp. of the Bay of Bengal, Bangladesh, for the first time. Endophytic fungi were identified taxonomically by morphologic...

Investigating endophytic fungi of Calotropis procera for novel bioactive compounds: molecular docking and bioactivity insights.

Microbial cell factories
BACKGROUND: The rising danger of antibiotic resistance and the increasing burden of cancer worldwide have highlighted the necessity for a constant supply of new antimicrobial drugs and anticancer therapies. Endophytic fungi, recognized as a rich supp...

From patterns to prediction: machine learning and antifungal resistance biomarker discovery.

Canadian journal of microbiology
Fungal pathogens significantly impact human health, agriculture, and ecosystems, with infections leading to high morbidity and mortality, especially among immunocompromised individuals. The increasing prevalence of antifungal resistance (AFR) exacerb...

Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques.

PloS one
Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art painting...

Machine learning models for predicting indoor airborne fungal concentrations in public facilities utilizing environmental variables.

Environmental pollution (Barking, Essex : 1987)
Airborne fungi are major contributors to substandard indoor air quality, with potential implications for public health, especially in public facilities. The risk of chronic exposure can be significantly reduced by accurately predicting airborne funga...

Superficial Fungal Infections and Artificial Intelligence: A Review on Current Advances and Opportunities: REVISION.

Mycoses
BACKGROUND: Superficial fungal infections are among the most common infections in world, they mainly affect skin, nails and scalp without further invasion. Superficial fungal diseases are conventionally diagnosed with direct microscopy, fungal cultur...

Modeling the latent impacts of extreme floods on indoor mold spores in residential buildings: Application of machine learning algorithms.

Environment international
Floods can severely impact the economy, environment and society. These impacts can be direct and indirect. Past research has focused more on the former impacts. Of the indirect impacts, those on mold growth in indoor environments that affect human re...

Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases.

Genome research
Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolution. However, eukaryotic populations...

Classification of Mycena and Species Using Deep Learning Models: An Ecological and Taxonomic Approach.

Sensors (Basel, Switzerland)
Fungi play a critical role in ecosystems, contributing to biodiversity and providing economic and biotechnological value. In this study, we developed a novel deep learning-based framework for the classification of seven macrofungi species from the ge...