PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Healthcare Informatics Research10.4258/hir.2021.27.3.2142021273214-221Machine Learning for Antibiotic Resistance Prediction: A Prototype Using Off-the-Shelf Techniques and Entry-Level Data to Guide Empiric Antimicrobial TherapyGeorgios Feretzakis, Aikaterini Sakagianni, Evangelos Loupelis, Dimitris Kalles, Nikoletta Skarmoutsou, Maria Martsoukou, Constantinos Christopoulos, Malvina Lada, Stavroula Petropoulou, Aikaterini Velentza, Sophia Michelidou, Rea Chatzikyriakou, Evangelos Dimitrelloshttp://e-hir.org/upload/pdf/hir-2021-27-3-214.pdf, http://e-hir.org/journal/view.php?doi=10.4258/hir.2021.27.3.214, http://e-hir.org/upload/pdf/hir-2021-27-3-214.pdf
Antimicrobial Stewardship & Healthcare Epidemiology10.1017/ash.2022.19020222S1s69-s69Using machine learning to predict antibiotic resistance to support optimal empiric treatment of urinary tract infectionsBen Brintz, McKenna Nevers, Matthew Goetz, Kelly Echevarria, Karl Madaras-Kelly, Matthew Samorehttps://www.cambridge.org/core/services/aop-cambridge-core/content/view/S2732494X22001905
International Journal of Antimicrobial Agents10.1016/s0924-8579(05)80212-2200526S75-S76A1.32 Bacterial spectrum and antibiotic resistance of uropathogens in hospitalized urological patients with urinary tract infections (1994–2004) and consequences for empiric antibiotic therapyhttps://api.elsevier.com/content/article/PII:S0924857905802122?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S0924857905802122?httpAccept=text/plain
International Journal of Antimicrobial Agents10.1016/j.ijantimicag.2023.1069662023106966Translation of Machine Learning–Based Prediction Algorithms to Personalized Empiric Antibiotic Selections: A Population-Based Cohort StudyChungsoo Kim, Young Hwa Choi, Jung Yoon Choi, Hee Jung Choi, Rae Woong Park, Sandy Jeong Rhiehttps://api.elsevier.com/content/article/PII:S0924857923002455?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S0924857923002455?httpAccept=text/plain
2023 3rd International Conference on Intelligent Technologies (CONIT)10.1109/conit59222.2023.102055832023Prediction Of Groundwater Level Using Advance Machine Learning TechniquesVivek Tiwari, Manikant Vermahttp://xplorestaging.ieee.org/ielx7/10205372/10205375/10205583.pdf?arnumber=10205583
10.21203/rs.3.rs-2820287/v12023Prediction of Autism spectrum disorder from high dimensional data using Machine Learning TechniquesArchana Pottem, G.N.V.G. Sirisha, R. Krishna Chaitanyahttps://www.researchsquare.com/article/rs-2820287/v1, https://www.researchsquare.com/article/rs-2820287/v1.html
Journal of Big Data10.1186/s40537-022-00657-5202291Chronic kidney disease prediction using machine learning techniquesDibaba Adeba Debal, Tilahun Melak Sitotehttps://link.springer.com/content/pdf/10.1186/s40537-022-00657-5.pdf, https://link.springer.com/article/10.1186/s40537-022-00657-5/fulltext.html, https://link.springer.com/content/pdf/10.1186/s40537-022-00657-5.pdf
2022 5th Asia Conference on Machine Learning and Computing (ACMLC)10.1109/acmlc58173.2022.000192022Prototype and Metric Based Prediction for Data-Efficient TrainingGaowei Zhouhttp://xplorestaging.ieee.org/ielx7/10221757/10221795/10221799.pdf?arnumber=10221799
Transportation Research Record: Journal of the Transportation Research Board10.1177/03611981187903722018267237141-152Multi-Level Driver Workload Prediction using Machine Learning and Off-the-Shelf SensorsPaul van Gent, Timo Melman, Haneen Farah, Nicole van Nes, Bart van Aremhttp://journals.sagepub.com/doi/pdf/10.1177/0361198118790372, http://journals.sagepub.com/doi/full-xml/10.1177/0361198118790372, http://journals.sagepub.com/doi/pdf/10.1177/0361198118790372
JAC-Antimicrobial Resistance10.1093/jacamr/dlz055201912Antimicrobial resistance: improving antibiotic stewardship by multi-disciplinary learninghttp://academic.oup.com/jacamr/article-pdf/1/2/dlz055/38275096/dlz055.pdf, http://academic.oup.com/jacamr/article-pdf/1/2/dlz055/38275096/dlz055.pdf