AI Medical Compendium Topic

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Decision Trees

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Topology identification in distribution system via machine learning algorithms.

PloS one
This paper contributes to the literature on topology identification (TI) in distribution networks and, in particular, on change detection in switching devices' status. The lack of measurements in distribution networks compared to transmission network...

Exploration of machine learning techniques to examine the journey to neuroendocrine tumor diagnosis with real-world data.

Future oncology (London, England)
Machine learning reveals pathways to neuroendocrine tumor (NET) diagnosis. Patients with NET and age-/gender-matched non-NET controls were retrospectively selected from MarketScan claims. Predictors (e.g., procedures, symptoms, conditions for which...

Construction data mining methods in the prediction of death in hemodialysis patients using support vector machine, neural network, logistic regression and decision tree.

Journal of preventive medicine and hygiene
OBJECTIVES: Chronic kidney disease (CKD) is one of the main causes of morbidity and mortality worldwide. Detecting survival modifiable factors could help in prioritizing the clinical care and offers a treatment decision-making for hemodialysis patien...

Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Computational and mathematical methods in medicine
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based...

Prediction of COVID-19 with Computed Tomography Images using Hybrid Learning Techniques.

Disease markers
Reverse Transcription Polymerase Chain Reaction (RT-PCR) used for diagnosing COVID-19 has been found to give low detection rate during early stages of infection. Radiological analysis of CT images has given higher prediction rate when compared to RT-...

Multi-label classification and label dependence in in silico toxicity prediction.

Toxicology in vitro : an international journal published in association with BIBRA
Most computational predictive models are specifically trained for a single toxicity endpoint and lack the ability to learn dependencies between endpoints, such as those targeting similar biological pathways. In this study, we compare the performance ...

Features Guided Face Super-Resolution via Hybrid Model of Deep Learning and Random Forests.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Face hallucination or super-resolution is a practical application of general image super-resolution which has been recently studied by many researchers. The challenge of good face hallucination comes from a variety of poses, illuminations, facial exp...

Machine learning-based decision tree classifier for the diagnosis of progressive supranuclear palsy and corticobasal degeneration.

Neuropathology and applied neurobiology
AIMS: This study aimed to clarify the different topographical distribution of tau pathology between progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD) and establish a machine learning-based decision tree classifier.