AIMC Topic: Malaysia
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Evaluating the transferability of low-cost sensor calibration using ANFIS: a field study in Putrajaya, Malaysia.
Environmental monitoring and assessment
Jul 31, 2025
This study evaluates the robustness of a previously developed calibration model for low-cost ozone sensors, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). The model was deployed at a different site without retraining. It was tested in Pu...
Evaluating the Usability of an HIV Prevention Artificial Intelligence Chatbot in Malaysia: National Observational Study.
JMIR human factors
Jul 15, 2025
BACKGROUND: Malaysia, an upper middle-income country in the Asia-Pacific region, has an HIV epidemic that has transitioned from needle sharing to sexual transmission, mainly in men who have sex with men (MSM). MSM are the most vulnerable population f...
Analyzing Patient Complaints in Web-Based Reviews of Private Hospitals in Selangor, Malaysia, Using Large Language Model-Assisted Content Analysis: Mixed Methods Study.
JMIR formative research
Jun 27, 2025
BACKGROUND: Large language model (LLM)-assisted content analysis (LACA) is a modification of traditional content analysis, leveraging the LLM to codevelop codebooks and automatically assign thematic codes to a web-based reviews dataset.
Enhanced cardiovascular risk prediction in the Western Pacific: A machine learning approach tailored to the Malaysian population.
PloS one
Jun 17, 2025
BACKGROUND: Cardiovascular disease (CVD) is a significant public health challenge in the Western Pacific region, including Malaysia.
Machine Learning Models for Predicting Type 2 Diabetes Complications in Malaysia.
Asia-Pacific journal of public health
Apr 18, 2025
This study aimed to develop machine learning (ML) models to predict diabetic complications in patients with type 2 diabetes (T2D) in Malaysia. Data from the Malaysian National Diabetes Registry and Death Register were used to develop predictive model...
Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence: Results of Hand-Crafted, Deep Radiomics Features and Radiologists' Assessment in Multicenter Cohorts.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Feb 15, 2025
OBJECTIVE: To develop, test, and externally validate a hybrid artificial intelligence (AI) model based on hand-crafted and deep radiomics features extracted from B-mode ultrasound images in differentiating benign and malignant thyroid nodules compare...
Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine).
Scientific reports
Jan 24, 2025
The COVID-19 pandemic has burdened healthcare systems globally. To curb high hospital admission rates, only patients with genuine medical needs are admitted. However, machine learning (ML) models to predict COVID-19 hospitalization in Asian children ...
Enhancing Small-for-Gestational-Age Prediction: Multi-Country Validation of Nuchal Thickness, Estimated Fetal Weight, and Machine Learning Models.
Prenatal diagnosis
Jan 16, 2025
OBJECTIVE: The first objective is to develop a nuchal thickness reference chart. The second objective is to compare rule-based algorithms and machine learning models in predicting small-for-gestational-age infants.
Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models.
Scientific reports
Dec 2, 2024
A significant portion of the world's population relies on rice as a primary source of nutrition. In Malaysia, rice production began in the early 1960s, which led to the cultivation of the country's most significant food crop up till the present day. ...
Traffic noise prediction model using GIS and ensemble machine learning: a case study at Universiti Teknologi Malaysia (UTM) Campus.
Environmental science and pollution research international
Oct 12, 2024
This study represents a pioneering effort to integrate geographic information systems (GIS) and ensemble machine learning methods to predict noise levels on a university campus. Three ensemble models including random forest (RF), gradient boosting (G...
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