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- **Machine learning models predicting multidrug resistant urinary tract infections using “DsaaS”**¹: This is a research paper that describes how to use a cloud platform called DSaaS (Data Science as a Service) to build predictive models for multidrug resistant UTIs using different machine learning methods such as Catboost, Support Vector Machine and Neural Networks.
- **The Use of Artificial Intelligence Algorithms in the Diagnosis of Urinary Tract Infections—A Literature Review**²: This is a review article that summarizes the current views and attempts to apply artificial intelligence techniques in UTI diagnosis, such as decision support systems, natural language processing and deep learning.
- **Predicting urinary tract infections in the emergency department using machine learning**³: This is another research paper that reports how to develop models for UTI prediction in the emergency department using six machine learning algorithms and various clinical variables.
- **A Clinical Prediction Tool for Extended-Spectrum Cephalosporin Resistance in Community-Onset Enterobacterales Urinary Tract Infection**⁴: This is a study that proposes a clinical prediction tool for antibiotic resistance in UTIs based on logistic regression and random forest models using patient characteristics and urine dipstick results.
- **Prediction of risk of acquiring urinary tract infection during hospitalization using machine learning**⁵: This is a recent paper that presents how to predict the risk of acquiring UTIs during hospitalization using five machine learning algorithms and data from electronic medical records.
I hope this helps you find what you are looking for.😊
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Source:
(1) Machine learning models predicting multidrug resistant urinary tract .... https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03566-7.
(2) JCM | Free Full-Text | The Use of Artificial Intelligence ... - MDPI. https://www.mdpi.com/2077-0383/11/10/2734.
(3) Predicting urinary tract infections in the emergency ... - PubMed. https://pubmed.ncbi.nlm.nih.gov/29513742/.
(4) A Clinical Prediction Tool for Extended-Spectrum Cephalosporin ... - PubMed. https://pubmed.ncbi.nlm.nih.gov/31041359/.
(5) Prediction of risk of acquiring urinary tract infection during ... - PLOS. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0248636.
Yes, there are several free AI tools available for the prediction of urinary tract infections (UTIs) based on dipstick tests and sediment analysis. These tools utilize machine learning algorithms to analyze the patterns and characteristics in urine dipstick results and sediment samples to predict the likelihood of UTIs. They can provide valuable insights and assist in diagnosing UTIs more accurately and efficiently. Some examples of free AI tools for UTI prediction include open-source projects like PyCaret, scikit-learn, and TensorFlow, which offer a wide range of machine learning algorithms and tools for developing UTI prediction models based on dipstick and sediment data.
https://www.researchgate.net/profile/Eugene-Lutsenko
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