The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
IJACSA research on disease prediction and diagnosis using machine learning and AI — covering heart, liver, kidney, respiratory, skin, and infectious disease prediction models.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed August 2026
As the continuous advancement of medical technology, image fusion technology has also been used in it. However, current medical image fusion systems still have drawbacks such as low image clarity, low accuracy, and slow…
Glaucoma is a common eye condition that can cause irreversible blindness if left untreated. Glaucoma can be identified by the optic nerve disorder (a perilous path that carries the potential risk) and leads to blindness.…
Climate change is one of the most talked-about topics of this decade, affecting all economic output sectors, including the economy of cow farming. In many scenarios, exceptionally severe climate change is predicted for t…
Chronic kidney disease (CKD) is a serious chronic illness without a definitive cure. According to WHO in 2015, 10% of the population suffers from CKD, with 1.5 million patients undergoing global haemodialysis. The incide…
The increasing use of electronic health records (EHRs) has led to a surge in unstructured data, making it challenging to extract valuable insights. This study proposes Natural Language Processing (NLP) based techniques t…
Cardiovascular disease (CVD) remains one of the leading causes of mortality worldwide, highlighting the need for early and precise prediction to support timely intervention. This study introduces an ensemble-based adapti…
During the Hajj season, Saudi Arabia experiences the arrival of millions of pilgrims from diverse linguistic and geographical backgrounds. This influx poses significant challenges for emergency medical care services. The…
Detecting wheat diseases and pests, particularly those characterized by small targets amidst complex background interference, presents a significant challenge in agricultural re-search. To address this issue and achieve…
Imbalanced datasets pose significant challenges in healthcare for developing accurate predictive models in medical diagnostics. In this work, we explore the effectiveness of combining resampling methods with machine lear…
In order to minimize the stochasticity of agents used in disease diagnosis within the dialogue system, and to enable them to interact with users based on the inherent connections between symptoms and diseases, while simu…
