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
Seizures are a serious neurological disease, and proper prognosis by electroencephalography (EEG) dramatically enhances patient outcomes. Current seizure prediction methods fail to deal with big data and usually need int…
Early and accurate classification of skin lesions is critical for effective skin cancer diagnosis and treatment. However, the visual similarity of lesions in their early stages often leads to misdiagnoses and delayed int…
The Internet of Medical Things (IoMT) is transforming healthcare through extensive automation, data collection, and real-time communication among interconnected devices. However, this rapid expansion introduces significa…
Plant disease detection is a crucial technology to ensure agricultural productivity and sustainability. However, traditional methods tend to fail as they do not address imprecise and uncertain data in a satisfactory way.…
Correct precision techniques have far not been introduced for modeling the modality risk in Intensive Care Unit (ICU) patients. Traditional mortality risk prediction techniques effectively extract the data in longitudina…
Alzheimer's Disease (AD) is a persistent, irreversible, and degenerative neurological disorder of the brain that currently has no effective therapy. This condition is identified by pathological abnormalities in the hippo…
In smart cities, the e-healthcare systems aided by Internet of Things (IoT) technologies play a significant role in proficient health monitoring services. The sensitivity and number of users in health networks highlights…
Cardiovascular disease is a critical threat to human health, as most death cases are due to heart disease. Although several doctors employ stethoscopes to auscultate heart sounds to detect abnormalities, the accuracy of…
Timely and accurate tumor detection in medical imaging is crucial for improving patient outcomes and reducing mortality rates. Traditional methods often rely on manual image interpretation, which is time-intensive and pr…
This research focuses on predicting Wisconsin Breast Cancer Disease using machine learning algorithm, employs a dataset offered by UCI repository (WBCD) dataset. The under- gone substantial preparation, includes managing…
