Leptospirosis modelling using hydrometeorological indices and random forest machine learning
Leptospirosis is a zoonosis that has been linked to hydrometeorological variability. Hydrometeorological averages and extremes have been used before as drivers in the statistical prediction of disease. However, their importance and predictive capacity are still little known. In this study, the use o...
Main Authors: | Jayaramu, Veianthan, Zulkafli, Zed, De Stercke, Simon, Buytaert, Wouter, Rahmat, Fariq, Abdul Rahman, Ribhan Zafira, Ishak, Asnor Juraiza, Tahir, Wardah, Ab Rahman, Jamalludin, Mohd Fuzi, Nik Mohd Hafiz |
---|---|
Format: | Article |
Published: |
Springer Science and Business Media
2023
|
Similar Items
-
The potential of eight plasma proteins as biomarkers in redefining leptospirosis diagnosis
by: Fish-Low, Cheng-Yee, et al.
Published: (2024) -
Site suitability assessment for selected nature-based solution (NBS) in flood-prone area
by: Ibrahim, Balqis, et al.
Published: (2024) -
Diversity of Wild Gingers (Zingiberaceae) in Southern Peninsular Malaysia: Panti Forest Reserve and Labis Forest
Reserve
by: Sedek, Aimi Syazana, et al.
Published: (2024) -
Basis risk reduction in weather index insurance for rice production in North-West Malaysia
by: Abdi, Mukhtar Jibril, et al.
Published: (2024) -
Unveiling the diversity and ecological roles of Macrofungi in Ayer Hitam Forest Reserve, Selangor, Malaysia
by: Noor Aisyah Mohd Nordin,, et al.
Published: (2024)