AIMC Topic: Random Forest

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Predicting dry weight change in Hemodialysis patients using machine learning.

BMC nephrology Jun 29, 2023
BACKGROUND: Machine Learning has been increasingly used in the medical field, including managing patients undergoing hemodialysis. The random forest classifier is a Machine Learning method that can generate high accuracy and interpretability in the d...
Body Weight Changes Japan Asian Renal Dialysis Blood Pressure Random Forest Humans Machine Learning Body Weight
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Prediction of stock price movement using an improved NSGA-II-RF algorithm with a three-stage feature engineering process.

PloS one Jun 28, 2023
Prediction of stock price has been a hot topic in artificial intelligence field. Computational intelligent methods such as machine learning or deep learning are explored in the prediction system in recent years. However, making accurate predictions o...
Random Forest Movement Machine Learning Artificial Intelligence Algorithms
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Artificial Intelligence Applied to a First Screening of Naevoid Melanoma: A New Use of Fast Random Forest Algorithm in Dermatopathology.

Current oncology (Toronto, Ont.) Jun 23, 2023
Malignant melanoma (MM) is the "great mime" of dermatopathology, and it can present such rare variants that even the most experienced pathologist might miss or misdiagnose them. Naevoid melanoma (NM), which accounts for about 1% of all MM cases, is a...
Melanoma Random Forest Artificial Intelligence Algorithms Melanoma, Cutaneous Malignant Humans
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Machine learning based canine posture estimation using inertial data.

PloS one Jun 21, 2023
The aim of this study was to design a new canine posture estimation system specifically for working dogs. The system was composed of Inertial Measurement Units (IMUs) that are commercially available, and a supervised learning algorithm which was deve...
Random Forest Machine Learning Walking Algorithms Animals Dogs Posture
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A Machine Learning Model Ensemble for Mixed Power Load Forecasting across Multiple Time Horizons.

Sensors (Basel, Switzerland) Jun 8, 2023
The increasing penetration of renewable energy sources tends to redirect the power systems community's interest from the traditional power grid model towards the smart grid framework. During this transition, load forecasting for various time horizons...
Machine Learning Algorithms Neural Networks, Computer Forecasting Random Forest
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Development of a 2D-QSAR Model for Tissue-to-Plasma Partition Coefficient Value with High Accuracy Using Machine Learning Method, Minimum Required Experimental Values, and Physicochemical Descriptors.

European journal of drug metabolism and pharmacokinetics Jun 2, 2023
BACKGROUND: The demand for physiologically based pharmacokinetic (PBPK) model is increasing currently. New drug application (NDA) of many compounds is submitted with PBPK models for efficient drug development. Tissue-to-plasma partition coefficient (...
Machine Learning Quantitative Structure-Activity Relationship Drug Development Plasma Random Forest
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Forward propagation dropout in deep neural networks using Jensen-Shannon and random forest feature importance ranking.

Neural networks : the official journal of the International Neural Network Society May 29, 2023
Dropout is a mechanism to prevent deep neural networks from overfitting and improving their generalization. Random dropout is the simplest method, where nodes are randomly terminated at each step of the training phase, which may lead to network accur...
Random Forest Neural Networks, Computer
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Machine Learning and Electroencephalogram Signal based Diagnosis of Dipression.

Neuroscience letters May 29, 2023
Depression is a psychological condition which hampers day to day activity (Thinking, Feeling or Action). The early detection of this illness will help to save many lives because it is now recognized as a global problem which could even lead to suicid...
Depression Decision Trees Electroencephalography Random Forest Datasets as Topic Depressive Disorder, Major Humans Neural Networks, Computer Case-Control Studies Machine Learning
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Process identification and discrimination in the environmental dose rate time series of a radiopharmaceutical facility using machine learning techniques.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine May 25, 2023
Multi-facility nuclear sites with research reactors have several environmental area gamma monitors in a network as a part of their surveillance capability. However, the routine release of low levels of Ar gas from the reactor is prone to interfere wi...
Random Forest Radiopharmaceuticals Algorithms Machine Learning Time Factors
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Prospective Validation of Machine Learning Algorithms for Absorption, Distribution, Metabolism, and Excretion Prediction: An Industrial Perspective.

Journal of chemical information and modeling May 22, 2023
Absorption, distribution, metabolism, and excretion (ADME), which collectively define the concentration profile of a drug at the site of action, are of critical importance to the success of a drug candidate. Recent advances in machine learning algori...
Rats Random Forest Solubility Animals Drug Discovery Algorithms Humans Machine Learning
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