BACKGROUND: Medical feature extraction from clinical text is challenging because of limited data availability, variability in medical terminology, and the critical need for trustworthy outputs. Large language models (LLMs) offer promising capabilitie...
The remote Objective Structured Clinical Examination (OSCE) is a cornerstone of medical education, enabling structured and objective assessment of clinical skills, communication, and patient-centered care. However, its widespread adoption has introdu...
This paper proposes the use of machine learning models to predict one's risk of having hypertension in the future using their routine health checkup data of their current and past visits to a health checkup center. The large-scale and high-dimensiona...
BACKGROUND: With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical tre...
BACKGROUND: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first p...
Roboticists often imbue robots with human-like physical features to increase the likelihood that they are afforded benefits known to be associated with anthropomorphism. Similarly, deepfakes often employ computer-generated human faces to attempt to c...
The number of robot-assisted minimally invasive surgeries is increasing annually, together with the need for dedicated and effective training. Surgeons need to learn how to address the novel control modalities of surgical instruments and the loss of ...
Artificial intelligence (AI) is infiltrating nearly all fields of science by storm. One notorious property that AI algorithms bring is their so-called black box character. In particular, they are said to be inherently unexplainable algorithms. Of cou...
Manifold visualisation techniques are commonly used to visualise high-dimensional datasets in physical sciences. In this paper, we apply a recently introduced manifold visualisation method, slisemap, on datasets from physics and chemistry. slisemap c...
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