The role of artificial intelligence, machine learning and deep learning in the diagnosis, prognosis and treatment of cancers primarily associated with women

Saxena, Ankur; Saxena, Mohit; Srivastava, Dhaval Kumar; Singh, Aditya Vikram; Sharma, Kaamya

doi:10.1515/9783110762044-010

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…AI enhances GIS by providing advanced algorithms for data processing, classification, and predictive modelling [15]. According to a study by Qamar et al (2023) [16] AI techniques, such as machine learning and deep learning, have been successfully applied to extract information from remotely sensed data, improving the accuracy and efficiency of land cover classification and change detection [82]. This synergy between AI and GIS facilitates the identification of critical habitats, migration patterns, and ecological changes, supporting informed decision-making in biodiversity conservation [83].…”

Section: Use Of Artificial Intelligentmentioning

confidence: 99%

Optimizing Biodiversity Conservation in Sundaland through Advanced Geospatial Techniques and Remote Sensing Technologies

Gabi,

Abdullah

2024

BIO Web Conf.

View full text Add to dashboard Cite

Sundaland ecosystems are under threat from human activity and climate change such as logging, agricultural practices, overexploitation of wildlife and climatic change that have led to frequent forest fires and a decline in indigenous plant and animal species. This study investigates the risks to Sundaland's biodiversity as well as the management possibilities using GIS, RS, and AI. The goal was to find out how artificial intelligence (AI) can be applied to effectively manage biodiversity and expand on the body of knowledge already available about the useful roles that GIS and RS play in the area. In this systematic method, seven databases were used to gather data from 110 research publications, of which 101 were screened for scope and subject variable. 80% (81articles) of the examined studies collected data using GIS and RS. It is found that. AI in biodiversity management is poised to grow, offering new opportunities to address the intricate challenges facing our planet's diverse ecosystems. In conclusion, for efficient monitoring, well-informed policy creation, and decision-making to guarantee the long-term preservation of Sundaland's biodiversity, integration of GIS, RS, and AI is essential.

show abstract