This dataset comprises a comprehensive collection of PubMed abstracts and associated metadata focusing on the topic of multiple sclerosis (MS) in relation to social determinants and environmental factors, spanning publications from January 1, 2018, to November 15, 2024.
This dataset contains MRI scans from 5 MS and 5 NMO cases from the Universiti Teknologi MARA (UiTM) hospital Malaysia. The brain lesions in the MRI scans have been annotated by a consultant radiologist from Pakistan Institute of Medical Sciences (PIMS) Islamabad Pakistan. The ground truth lesion masks are available as png files, whereas the brain scans are available as jpg files.
Falls are a major health problem with one in three people over the age of 65 falling each year, oftentimes causing hip fractures, disability, reduced mobility, hospitalization and death. A major limitation in fall detection algorithm development is an absence of real-world falls data. Fall detection algorithms are typically trained on simulated fall data that contain a well-balanced number of examples of falls and activities of daily living. However, real-world falls occur infrequently, making them difficult to capture and causing severe data imbalance.
