Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

In AIoT-based systems, sensors continuously collect high-frequency data such as vibration, temperature, pressure, and electrical signals. These data streams are processed by machine learning and deep ...

Your neighbor has a gorgeous shade tree with branches that stretch across the fence-line. For a few months, you appreciate the shade, shelter, and brilliant fall color this tree provides. But then ...

Abstract: K-Nearest Neighbors (KNN) is a basic model in a ML field used for classification or prediction analysis owing to its efficiency. The following paper will be a survey paper focused on ...

It is unclear who benefits the most from atherosclerotic cardiovascular disease (ASCVD) screening imaging. This study aimed to identify features associated with positive coronary artery calcium scores ...

Background: Distant metastasis is a key factor contributing to poor prognosis in renal cell carcinoma (RCC). Early prediction of metastasis is crucial for developing personalized treatment plans and ...

Maritime cargo capacity serves as a critical indicator of port efficiency and regional economic impact, yet reliable data remain constrained by operational and commercial complexities. This study ...