AIMC Topic: Decision Trees

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

Biomedical physics & engineering express Mar 26, 2025
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...
Bayes Theorem Wounds and Injuries Support Vector Machine Wound Healing Decision Trees Artificial Intelligence Algorithms Humans
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Employing artificial bee and ant colony optimization in machine learning techniques as a cognitive neuroscience tool.

Scientific reports Mar 24, 2025
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...
Decision Trees Bees Ants Cognitive Neuroscience Algorithms Humans Animals Machine Learning Students
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Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy.

Scientific reports Mar 21, 2025
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...
Decision Trees Bayes Theorem Discriminant Analysis Biopsy Lung Neoplasms Support Vector Machine Bronchoscopy Dielectric Spectroscopy Humans Machine Learning Algorithms Middle Aged ROC Curve Female Male
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Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).

BMC psychiatry Mar 18, 2025
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...
Algorithms Female Aged Adult Humans Machine Learning Depression Inpatients Decision Trees Middle Aged Comorbidity Anxiety Sensitivity and Specificity Gastrointestinal Diseases Anxiety Disorders Male Gastroenterology
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Predicting pregnancy at the first year following metabolic-bariatric surgery: development and validation of machine learning models.

Surgical endoscopy Mar 10, 2025
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...
Humans Machine Learning Case-Control Studies Decision Trees Bariatric Surgery Pregnancy Obesity, Morbid Female Adult
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A new approach to dilution prediction of underground mine gold using computing techniques.

Anais da Academia Brasileira de Ciencias Mar 3, 2025
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...
Decision Trees Machine Learning Brazil Gold Environmental Monitoring Mining
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Machine Learning-Driven Modeling to Predict Postdischarge Venous Thromboembolism After Pancreatectomy for Pancreas Cancer.

Annals of surgical oncology Feb 20, 2025
BACKGROUND: Postdischarge venous thromboembolism (pdVTE) is a life-threatening complication following resection for pancreatic cancer (PC). While national guidelines recommend extended chemoprophylaxis for all, adherence is low and ranges from 1.5 to...
Prognosis Patient Discharge Retrospective Studies Venous Thromboembolism Postoperative Complications Humans Pancreatectomy Female Aged Follow-Up Studies Machine Learning Male Risk Factors Decision Trees Middle Aged Pancreatic Neoplasms
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Optimized machine learning framework for cardiovascular disease diagnosis: a novel ethical perspective.

BMC cardiovascular disorders Feb 20, 2025
Alignment of advanced cutting-edge technologies such as Artificial Intelligence (AI) has emerged as a significant driving force to achieve greater precision and timeliness in identifying cardiovascular diseases (CVDs). However, it is difficult to ach...
Predictive Value of Tests Humans Diagnosis, Computer-Assisted Machine Learning Reproducibility of Results Decision Trees Decision Support Techniques Cardiovascular Diseases
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[Validation of a decision tree for selective dry cow therapy of dairy for a digital expert system].

Tierarztliche Praxis. Ausgabe G, Grosstiere/Nutztiere Feb 18, 2025
In this study, a decision tree derived from scientific literature on selective dry cow therapy (ST), which was developed as a knowledge base for a digital expert system, was evaluated. The decision tree merges algorithmic (based on cell count results...
Decision Trees Anti-Bacterial Agents Lactation Female Milk Mammary Glands, Animal Mastitis, Bovine Animals Dairying Cattle Expert Systems Germany
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Predicting preterm birth using machine learning methods.

Scientific reports Feb 16, 2025
Preterm birth is a significant public health concern, given its correlation with neonatal mortality and morbidity. The aetiology of preterm birth is complex and multifactorial. The objective of this study was to develop and compare machine learning m...
Premature Birth Adult Algorithms Logistic Models Pregnancy Support Vector Machine Humans Female Decision Trees Machine Learning Infant, Newborn
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