[HTML][HTML] Blockchain and artificial intelligence technology in e-Health

P Tagde, S Tagde, T Bhattacharya, P Tagde… - … Science and Pollution …, 2021 - Springer
Blockchain and artificial intelligence technologies are novel innovations in healthcare
sector. Data on healthcare indices are collected from data published on Web of Sciences …

Rulers of the world, unite! The challenges and opportunities of artificial intelligence

A Kaplan, M Haenlein - Business Horizons, 2020 - Elsevier
A decade ago, we published an article in Business Horizons about the challenges and
opportunities of social media with a call to action:“Users of the world, unite!” To celebrate its …

Artificial intelligence in drug development: present status and future prospects

KK Mak, MR Pichika - Drug discovery today, 2019 - Elsevier
Highlights•Advances in artificial intelligence (AI) are modernising several aspects of our
lives.•The pharma industry is facing challenges to overcome the high attrition rates in drug …

[HTML][HTML] Deep learning and artificial intelligence in sustainability: a review of SDGs, renewable energy, and environmental health

Z Fan, Z Yan, S Wen - Sustainability, 2023 - mdpi.com
Artificial intelligence (AI) and deep learning (DL) have shown tremendous potential in
driving sustainability across various sectors. This paper reviews recent advancements in AI …

[HTML][HTML] Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges

M Chen, C Claramunt, A Çöltekin, X Liu, P Peng… - Earth-Science …, 2023 - Elsevier
In recent decades, we have witnessed great advances on the Internet of Things, mobile
devices, sensor-based systems, and resulting big data infrastructures, which have gradually …

[HTML][HTML] Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea

CC Lim, H Kim, MJR Vilcassim, GD Thurston… - Environment …, 2019 - Elsevier
Recent studies have demonstrated that mobile sampling can improve the spatial granularity
of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (< …

[HTML][HTML] An overview of GeoAI applications in health and healthcare

MN Kamel Boulos, G Peng, T VoPham - International journal of health …, 2019 - Springer
The moulding together of artificial intelligence (AI) and the geographic/geographic
information systems (GIS) dimension creates GeoAI. There is an emerging role for GeoAI in …

[HTML][HTML] A multimethod approach for county-scale geospatial analysis of emerging infectious diseases: a cross-sectional case study of COVID-19 incidence in …

C Scarpone, ST Brinkmann, T Große… - International journal of …, 2020 - Springer
Abstract Background As of 13 July 2020, 12.9 million COVID-19 cases have been reported
worldwide. Prior studies have demonstrated that local socioeconomic and built environment …

A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science

AL Balogun, A Tella, L Baloo, N Adebisi - Urban Climate, 2021 - Elsevier
Air pollution is a global geo-hazard with significant implications, including deterioration of
health and premature death. Climatic variables such as temperature, rainfall, wind, and …

[HTML][HTML] Geospatial data management research: Progress and future directions

M Breunig, PE Bradley, M Jahn, P Kuper… - … International Journal of …, 2020 - mdpi.com
Without geospatial data management, today's challenges in big data applications such as
earth observation, geographic information system/building information modeling (GIS/BIM) …