Machine learning for predicting medical outcomes associated with acute lithium poisoning
Abstract The use of machine learning algorithms and artificial intelligence in medicine has attracted significant interest due to its ability to aid in predicting medical outcomes. This study aimed to evaluate the effectiveness of the random forest algorithm in predicting medical outcomes related to...
Saved in:
| Main Authors: | Omid Mehrpour, Varun Vohra, Samaneh Nakhaee, Seyed Ali Mohtarami, Farshad M. Shirazi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-94395-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Lead poisoning and its effects on bone density
by: Alireza Zabihi, et al.
Published: (2025-05-01) -
Prolonged delirium caused by lithium poisoning in an endometrial cancer patient at advanced stage: A case report
by: Tomoya Natsuyama, et al.
Published: (2023-03-01) -
Acute medication poisoning in children at Alexandria Poison Centre, Egypt: an educational intervention
by: Mostafa Arafa, et al.
Published: (2025-06-01) -
On the Treatment of Acute Poisoning With Paracetamol
by: A. Yu. Simonova, et al.
Published: (2022-09-01) -
Characteristics of acute poisoning at two referral hospitals in Francistown and Gaborone
by: Ntambwe Malangu
Published: (2008-06-01)