Results 121 to 130 of about 73,492 (280)

Machine Learning Project : Naive Bayes Classifier

, 2019
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. This model is used on banking data to predict customers' decision about banking.
openaire   +1 more source

Interpretable machine learning enables early and accurate detection of drug‐induced liver injury: A multicenter study with real‐world clinical translation

Interdisciplinary Medicine, EarlyView.
This study develops an interpretable gradient‐boosting model that accurately identifies drug‐induced liver injury (DILI) using routine laboratory data. The model explains key clinical features through SHapley Additive exPlanations analysis and detects DILI earlier than expert evaluation, offering a transparent and practical tool for precision ...
Jingyi Ling, Shian Zhang, Jun Lin, Zhengju Xu, Runcheng Xu, Qian Lv, Kaixiang Zhang, Sheng Liu, Jie Guo, Cheng Hua, Yin Jia, Xiaoyu Xu, Kun Qian, Shanrong Liu   +13 more
wiley   +1 more source

Artificial Intelligence-Based Effective Detection of Parkinson’s Disease Using Voice Measurements

Engineering Proceedings
Parkinson’s disease (PD) is a neurodegenerative illness that affects the central nervous system and leads to a gradual degeneration of neurons that results in movement slowness, mental health problems, speaking difficulties, etc.
Gogulamudi Pradeep Reddy, Duppala Rohan, Yellapragada Venkata Pavan Kumar, Kasaraneni Purna Prakash, Mandarapu Srikanth   +4 more
doaj   +1 more source

Can naive Bayes classifier predict infection in a close contact of COVID-19? A comparative test for predictability of the predictive model and healthcare workers in Japan. [PDF]

J Infect Chemother, 2022
Yoshikawa H.
europepmc   +1 more source

Magnetocardiography combined with machine learning for pulmonary hypertension detection and improved short‐term risk assessment

Interdisciplinary Medicine, EarlyView.
Magnetocardiography (MCG) enables non‐invasive mapping of cardiac magnetic fields. In this study, an MCG‐based machine learning model detects pulmonary hypertension with robust performance. Furthermore, MCG features may improve the accuracy of short‐term risk assessment.
Yuankun Qi, Jiaqi Liang, Kai Ma, Xiaoyu Hu, Yu Zhang, Xiaole Han, Dong Xu, Xu Zhang, Xiaopei Cui, Min Xiang, Hongyu Zhang, Jiancheng Fang   +11 more
wiley   +1 more source

Protective Effects of Riociguat Against Contrast‐Induced Nephropathy: An Experimental and Machine Learning‐Based Study in Rats

The Kaohsiung Journal of Medical Sciences, EarlyView.
ABSTRACT Contrast‐induced nephropathy (CIN) is an important cause of acute kidney injury following exposure to iodinated contrast media, and effective preventive strategies remain limited. This study investigated the renoprotective effects of riociguat, a soluble guanylate cyclase stimulator, in an experimental rat model of CIN and explored machine ...
Mustafa Begenc Tascanov, Kenan Toprak, Sibel Turedi, İsmail Koyuncu, Zulkif Tanrıverdi, Necip Fazıl Dedeoglu, Halil Fedai, Asuman Bicer, İbrahim Halil Altıparmak, Recep Demirbag, Gencay Sarıısık   +10 more
wiley   +1 more source

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  

[Establishment of naive Bayes classifier-based risk prediction model for chemotherapyinduced nausea and vomiting]. [PDF]

Nan Fang Yi Ke Da Xue Xue Bao, 2021
Cao Z, Xiong X, Yang Q.
europepmc   +1 more source

Uncovering Key Characteristics of Antibacterial Peptides through Machine Learning

Macromolecular Rapid Communications, EarlyView.
Machine‐learning (ML) techniques using random forest classification models revealed key characteristics that predict effective antimicrobial peptides (AMPs) targeting Gram‐negative bacteria, Gram‐positive bacteria, and mycobacteria. The ideal cLogP (<$ < $−6) and net‐charge (≤+4) threshold was the same for all three targets with variations in the ...
Jooyoung Roh, Cyrille Boyer, Priyank V. Kumar   +2 more
wiley   +1 more source

From Data to Decisions: How Machine Learning and Generative Artificial Intelligence Are Redefining Precision Medicine in Kidney Transplantation

Organ Medicine, EarlyView.
This review evaluates how machine learning, multimodal integration, and generative AI optimize kidney transplant outcomes. These tools enable superior prediction and personalized therapy but face hurdles in data volume, generalizability, and ethics. Future clinical adoption depends on continued innovation and multidisciplinary collaboration to overcome
Maoxin Liao, Cheng Yang
wiley   +1 more source