BACKGROUND: Healthcare simulation is critical for medical education, with traditional methods using simulated patients (SPs). Recent advances in artificial intelligence (AI) offer new possibilities with AI-based simulators, introducing limitless oppo...
OBJECTIVES: To evaluate the diagnostic accuracy of machine learning models incorporating multimodal features for predicting radiation pneumonitis in lung cancer through a systematic review and meta-analysis.
BACKGROUND: Type II diabetes mellitus (T2DM) is strongly linked with a heightened risk of coronary artery disease (CAD). Exploring biological targets common to T2DM and CAD is essential for CAD intervention strategies.
Measurement techniques often result in domain gaps among batches of cellular data from a specific modality. The effectiveness of cross-batch annotation methods is influenced by inductive bias, which refers to a set of assumptions that describe the be...
This study evaluates the effectiveness of an Artificial Intelligence (AI)-based smartphone application designed for decay detection on intraoral photographs, comparing its performance to that of junior dentists. Conducted at The Aga Khan University H...
Knee osteoarthritis (KOA) represents a well-documented degenerative arthropathy prevalent among the elderly population. KOA is a persistent condition, also referred to as progressive joint Disease, stemming from the continual deterioration of cartila...
Deep learning involves an artificial intelligence (AI) approach and has been shown to provide superior performance for automating image recognition tasks, as well as exceeding human capabilities in both time and accuracy. Histopathology diagnostics i...
Self-supervised learning has become the cornerstone of building generalizable and transferable artificial intelligence systems in medical imaging. In particular, contrastive representation learning techniques trained on large multi-modal datasets hav...
Patients with end-stage kidney disease (ESKD) frequently experience anemia, and maintaining hemoglobin (Hb) levels within a targeted range using erythropoiesis-stimulating agents (ESAs) is challenging. This study introduces a gated recurrent unit-att...
Humans have been shown to have biases when reading medical images, raising questions about whether humans are uniform in their disease gradings. Artificial intelligence (AI) tools trained on human-labeled data may have inherent human non-uniformity. ...
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