AIMC Topic: Machine Learning

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A Machine Learning-Based Risk Score for Prediction of Infective Endocarditis Among Patients With Staphylococcus aureus Bacteremia-The SABIER Score.

The Journal of infectious diseases
BACKGROUND: Early risk assessment is needed to stratify Staphylococcus aureus infective endocarditis (SA-IE) risk among patients with S. aureus bacteremia (SAB) to guide clinical management. The objective of the current study was to develop a novel r...

[Application of machine learning models in schistosomiasis control: a review].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
Schistosomiasis is a major public health concern in the world, and precision control is crucial to combating this disease. Due to the complex and diverse transmission route of schistosomiasis, conventional statistical models have significant limitati...

[Progress in application of machine learning in epidemiology].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Population based health data collection and analysis are important in epidemiological research. In recent years, with the rapid development of big data, Internet and cloud computing, artificial intelligence has gradually attracted attention of epidem...

Machine learning assisted sorting of active microswimmers.

The Journal of chemical physics
Active matter systems, being in a non-equilibrium state, exhibit complex behaviors, such as self-organization, giving rise to emergent phenomena. There are many examples of active particles with biological origins, including bacteria and spermatozoa,...

Study of obesity research using machine learning methods: A bibliometric and visualization analysis from 2004 to 2023.

Medicine
BACKGROUND: Obesity, a multifactorial and complex health condition, has emerged as a significant global public health concern. Integrating machine learning techniques into obesity research offers great promise as an interdisciplinary field, particula...

Prediction of Glioma enhancement pattern using a MRI radiomics-based model.

Medicine
Contrast-MRI scans carry risks associated with the chemical contrast agents. Accurate prediction of enhancement pattern of gliomas has potential in avoiding contrast agent administration to patients. This study aimed to develop a machine learning rad...

Gene-Specific Machine Learning Models to Classify Driver Mutations in Clonal Hematopoiesis.

Cancer discovery
There is no general consensus on the set of mutations capable of driving the age-related clonal expansions in hematopoietic stem cells known as clonal hematopoiesis, and current variant classifications typically rely on rules derived from expert know...

Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis.

Cancer discovery
Clonal hematopoiesis (CH) is a phenomenon of clonal expansion of hematopoietic stem cells driven by somatic mutations affecting certain genes. Recently, CH has been linked to the development of hematologic malignancies, cardiovascular diseases, and o...