Results 141 to 150 of about 371,575 (291)

Naïve Bayes evidence accumulation K-modes clustering: A new method for classifying binary data and its application on real data of injecting drug users

Journal of Biostatistics and Epidemiology, 2018
Background & Aim: Clustering is the method of classifying discrete data such as Kmodes, and Naïve Bayes classifier is the classification to predict the unknown real classes.
Zahra Zamaninasab, Hamid Sharifi, Abbas Bahrampour   +2 more
doaj  

Bayes' Theorem and Naive Bayes Classifier

This article gives a mathematically rigorous yet easily accessible introduction to Bayes’ theorem and the foundations of naive Bayes learning. Starting from the fundamental elements of probability theory, this article outlines all steps leading to one of
Berrar, Daniel
core  

Zinc oxide/polydimethylsiloxane‐coated carbon fiber yarns for machine‐learning‐assisted gait classification

InfoScience, EarlyView.
Gait analysis can provide valuable information for identifying changes in movement associated with neurological disorders, thus serving as an important support tool in several areas, including healthcare and rehabilitation. In this study, zinc oxide/polydimethylsiloxane (ZnO/PDMS)‐coated carbon fiber yarns were developed and evaluated as pressure ...
Maria Morais, Raquel Barras, Jorge Martins, Ana Rovisco, Elvira Fortunato, Rodrigo Martins, Diana Gaspar, Hugo Gamboa, Emanuel Carlos, Luís Pereira, Pedro Barquinha   +10 more
wiley   +1 more source

A Comprehensive Study to Compare Different Compound Representations for Predicting Carcinogenicity In Vivo

Journal of Applied Toxicology, EarlyView.
ABSTRACT Carcinogenicity evaluation is a critical component of chemical risk assessment, yet traditional in vivo testing remains time consuming, costly, and ethically challenging. Computational approaches based on machine learning offer promising alternatives, but the relative contributions of different molecular representation strategies for ...
Iuri Barbosa Pereira, Rogerio Salvini, Eloisa Dutra Caldas   +2 more
wiley   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Optimization the Naive Bayes Classifier Method to Diagnose Diabetes Mellitus [PDF]

, 2019
World Health Organization (WHO) states that Diabetes Mellitus is the world's top deadly  disease. several studies in the health sector including diabetes mellitus have been carried out to detect diseases early.
Susilawati, D. S. (Desi), Riana, D. (Dwiza)   +1 more
core  

Machine Learning Project : Naive Bayes Classifier

, 2019
<p>This is Naive Bayes Classifier based on Maximum Likelihood Estimation. The first model is to handle categorical data only. The second model can handle both categorical data and numeric data.
Huang, Bixuan, Bixuan Huang
core   +1 more source

Explainable, Uncertainty‐Aware Machine Learning for Maize Land Suitability and Climate Resilience in Lorestan Province, Western Iran

Land Degradation &Development, EarlyView.
ABSTRACT Maize (Zea mays L.) is strategically important in Iran, yet its cultivation in the semi‐arid Zagros is constrained by limited and variable water, heat stress and heterogeneous soils, while conventional suitability assessments are deterministic, rarely validated spatially and provide no measure of confidence.
Ahad Madani, Narges Shafaei Bajestani
wiley   +1 more source

Implementasi Metode Naive Bayes Classifier Untuk Klasifikasi Penyakit Leukemia

, 2018
Penelitian ini bertujuan untuk merancang dan mengimplementasikan metode Naive Bayes Classifier sehingga dapat mengklasifikasikan penyakit leukemia.Data ini diperoleh dari (1) Penelitian Lapangan (2) Studi Pustaka (3) Wawancara. Data itu dianalisis dengan
Muhammad Jumardi Ngoyo
core  

Sleep‐Autonomic Interactions in Parkinson's Disease and Multiple System Atrophy: A Comparative Study Using Structural Equation Modeling

Movement Disorders Clinical Practice, EarlyView.
Abstract Background Parkinson's disease (PD) and multiple system atrophy (MSA) are α‐synucleinopathies with overlapping autonomic and sleep dysfunction, but distinct trajectories. Objectives This study compared sleep and autonomic profiles in PD and MSA and elucidated disease‐specific associations using structural equation modeling (SEM).
Bora Jin, Yoonkyung Lee, Seungho Lee, Byeol‐A Yoon, Young Jin Jeong, Sang‐Myung Cheon   +5 more
wiley   +1 more source