H.3. Artificial Intelligence
A New Hybrid Method to Detect Risk of Gastric Cancer using Machine Learning Techniques

Ali Zahmatkesh Zakariaee; Hossein Sadr; Mohamad Reza Yamaghani

Volume 11, Issue 4 , November 2023, , Pages 505-515

https://doi.org/10.22044/jadm.2023.13377.2464

Abstract
  Machine learning (ML) is a popular tool in healthcare while it can help to analyze large amounts of patient data, such as medical records, predict diseases, and identify early signs of cancer. Gastric cancer starts in the cells lining the stomach and is known as the 5th most common cancer worldwide. ...  Read More

H.3. Artificial Intelligence
LSTM Modeling and Optimization of Rice (Oryza sativa L.) Seedling Growth using Intelligent Chamber

Hamid Ghaffari; Hemmatollah Pirdashti; Mohammad Reza Kangavari; Sjoerd Boersma

Volume 11, Issue 4 , November 2023, , Pages 561-571

https://doi.org/10.22044/jadm.2023.13026.2451

Abstract
  An intelligent growth chamber was designed in 2021 to model and optimize rice seedlings' growth. According to this, an experiment was implemented at Sari University of Agricultural Sciences and Natural Resources, Iran, in March, April, and May 2021. The model inputs included radiation, temperature, carbon ...  Read More

H.3. Artificial Intelligence
Fast COVID-19 Infection Prediction with In-House Data Using Machine Learning Classification Algorithms: A Case Study of Iran

Ali Rebwar Shabrandi; Ali Rajabzadeh Ghatari; Nader Tavakoli; Mohammad Dehghan Nayeri; Sahar Mirzaei

Volume 11, Issue 4 , November 2023, , Pages 573-585

https://doi.org/10.22044/jadm.2023.13291.2458

Abstract
  To mitigate COVID-19’s overwhelming burden, a rapid and efficient early screening scheme for COVID-19 in the first-line is required. Much research has utilized laboratory tests, CT scans, and X-ray data, which are obstacles to agile and real-time screening. In this study, we propose a user-friendly ...  Read More

I.3.7. Engineering
Evaluation of liquefaction potential based on CPT results using C4.5 decision tree

A. Ardakani; V. R. Kohestani

Volume 3, Issue 1 , March 2015, , Pages 85-92

https://doi.org/10.5829/idosi.JAIDM.2015.03.01.09

Abstract
  The prediction of liquefaction potential of soil due to an earthquake is an essential task in Civil Engineering. The decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. C4.5 is a known algorithm widely used to design ...  Read More