Machine learning for prediction of viral hepatitis: A systematic review and meta-analysis

K Moulaei, H Sharifi, K Bahaadinbeigy… - International Journal of …, 2023 - Elsevier
Background Lack of accurate and timely diagnosis of hepatitis poses obstacles to effective
treatment, disease progression prevention, complication reduction, and life-saving …

An effective 3D text recurrent voting generator for metaverse

WH Park, NMF Qureshi, DR Shin - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Metaverse is a novel innovative platform that connects users worldwide in the distributed
virtual environment. People share their interests, opinions, and resources on this virtual …

[PDF][PDF] A survey of different machine learning models for Alzheimer disease prediction

R Davuluri, R Rengaswamy - Int J, 2020 - academia.edu
 ABSTRACT Machine learning model is one of the best disease prediction framework in
various medical disease prediction processes. Alzheimer's disease (AD) is a progressive …

[HTML][HTML] WT-CNN: a hybrid machine learning model for heart disease prediction

F Mohammad, S Al-Ahmadi - Mathematics, 2023 - mdpi.com
Heart disease remains a predominant health challenge, being the leading cause of death
worldwide. According to the World Health Organization (WHO), cardiovascular diseases …

Analisis Perbandingan Algoritma Bisecting K-Means dan Fuzzy C-Means pada Data Pengguna Kartu Kredit

S Dwididanti, DA Anggoro… - Emitor: Jurnal Teknik …, 2022 - journals.ums.ac.id
Di era digital seperti sekarang ini memiliki kartu kredit merupakan suatu hal yang wajar di
masyarakat, dengan segala kemudahan yang ditawarkan dalam setiap transaksi …

Implementation of machine learning using the k-nearest neighbor classification model in diagnosing malnutrition in children

M Ula, AF Ulva, I Saputra… - Multica Science …, 2022 - journal.universitasmulia.ac.id
The problem faced today is the lack of nutrition for children which causes stunting. One way
to prevent stunting problems is to provide input to the community in Aceh for the importance …

Intelligent fault classification of air compressors using Harris hawks optimization and machine learning algorithms

A Afia, F Gougam, C Rahmoune… - Transactions of the …, 2024 - journals.sagepub.com
Due to their complexity and often harsh working environment, air compressors are inevitably
exposed to a variety of faults and defects during their operation. Thus, condition monitoring …

[HTML][HTML] Diabetes classification using machine learning techniques

M Phongying, S Hiriote - Computation, 2023 - mdpi.com
Machine learning techniques play an increasingly prominent role in medical diagnosis. With
the use of these techniques, patients' data can be analyzed to find patterns or facts that are …

[PDF][PDF] AI-Enabled Grouping Bridgehead to Secure Penetration Topics of Metaverse.

WH Park, IF Siddiqui… - Computers, Materials & …, 2022 - cdn.techscience.cn
With the advent of the big data era, security issues in the context of artificial intelligence (AI)
and data analysis are attracting research attention. In the metaverse, which will become a …

[PDF][PDF] Implementation of K-nearest neighbors algorithm for predicting heart disease using python flask

DA Anggoro, NC Aziz - Iraqi Journal of Science, 2021 - iasj.net
Heart disease is a non-communicable disease and the number 1 cause of death in
Indonesia. According to WHO predictions, heart disease will cause 11 million deaths in …