AIMC Topic: Decision Trees

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Enlightened prognosis: Hepatitis prediction with an explainable machine learning approach.

PloS one
Hepatitis is a widespread inflammatory condition of the liver, presenting a formidable global health challenge. Accurate and timely detection of hepatitis is crucial for effective patient management, yet existing methods exhibit limitations that unde...

Evaluating how different balancing data techniques impact on prediction of premature birth using machine learning models.

PloS one
Premature birth can be defined as birth before 37 weeks of gestation, which is a significant global health issue, being the main cause for neonatal deaths. In this work, we evaluate machine learning models for predicting premature birth using Brazili...

Intelligent progress monitoring of healing wound tissues based on classification models.

Biomedical physics & engineering express
The evolution of wound monitoring techniques has seen a significant shift from traditional methods like ruler-based measurements to the use of AI-assisted assessment of wound tissues. This progression has been driven by the need for more accurate, ef...

Employing artificial bee and ant colony optimization in machine learning techniques as a cognitive neuroscience tool.

Scientific reports
Higher education is essential because it exposes students to a variety of areas. The academic performance of IT students is crucial and might fail if it isn't documented to identify the features influencing them, as well as their strengths and shortc...

Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy.

Scientific reports
New bronchoscopy techniques like radial probe endobronchial ultrasound have been developed for real-time sampling characterization, but their use is still limited. This study aims to use classification algorithms with minimally invasive electrical im...

Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).

BMC psychiatry
BACKGROUND: Accurately diagnosing Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) shows significant challenges as traditional diagnostic methods fail to meet expectations due to patient hesitance and non-psychiatric h...

Predicting pregnancy at the first year following metabolic-bariatric surgery: development and validation of machine learning models.

Surgical endoscopy
BACKGROUND: Metabolic-bariatric surgery (MBS) is the last effective way to lose weight whom around half of the patients are women of reproductive age. It is recommended an interval of 12 months between surgery and pregnancy to optimize weight loss an...

A new approach to dilution prediction of underground mine gold using computing techniques.

Anais da Academia Brasileira de Ciencias
Controlling ore dilution in underground mining is challenging. In this study, data from a Brazilian gold mine were analyzed, covering 70 chambers and 26 variables. Six key variables were identified through decision tree analysis, forming the basis of...