This research introduces a novel approach to Alzheimer's disease detection by combining
Xception's efficiency with machine learning classifiers, notably XGBoost. The hybrid model …

With the deployment of Electronic Health Records, much effort is being devoted to the
development of Natural Language Processing tools that convert information described in …

In recent years, the number of motor vehicle accidents has been increasing, causing
significant morbidity and mortality worldwide. This study proposes a machine learning model …

The expanding landscape of cyber threats, alongside the diminished effectiveness of
traditional detection methods, has necessitated the exploration of machine learning (ML) …

Learning from real-world clinical data has potential to promote the quality of care, improve
the efficiency of healthcare systems, and support clinical research. As a large proportion of …

Identification of risks ahead of MRI examinations is identified as a cumbersome and time-
consuming process at the Linköping University Hospital radiology clinic. The hospital staff …

Pathology reports provide valuable information for cancer registries to understand, plan and
implement strategies to mitigate the impact of cancer. However, coding key information from …

Clinical text classification is the process of extracting the information from clinical narratives.
Clinical narratives are the voice files, notes taken during a lecture, or other spoken material …

The electronic health record (EHR) is an unavoidable and vital tool for the medical and
behavioral health professionals. It is difficult to imagine what patient care would appear like …

Background: Evaluate the consistency of information in paper-based records when
registered in parallel with an electronic medical record. Methods: The study was performed …