OBJECTIVES: To develop a multidimensional clinical indicator-based prediction model for identifying high-risk patients with fertilization failure conventional in vitro fertilization (c-IVF) cycles, thereby optimizing therapeutic decision-making.
BACKGROUND: The healthcare sector is undergoing a digital transformation, where the integration of Artificial Intelligence (AI) plays a vital role in reshaping healthcare practices. AI technologies promise to improve work procedures, mitigate future ...
BACKGROUND: The integration of artificial intelligence (AI) into healthcare has led to promising advancements in clinical decision-making and diagnostic accuracy. In dentistry, automated methods to evaluate oral hygiene measures, such as dental plaqu...
BACKGROUND: Crisis support services offer crucial intervention for individuals in acute distress, providing timely access to trained volunteers whose human connection is key to the effectiveness of these services. However, there are significant dispa...
BACKGROUND: Human Immunodeficiency Virus (HIV) pre-exposure prophylaxis (PrEP) prevents HIV transmission but has low uptake among women. Identifying women who could benefit from PrEP remains a challenge. This study developed a women-specific model to...
BACKGROUND: Machine learning algorithms may contribute to improving maternal and child health, including determining the suitability of caesarean section (CS) births in low-resource countries. Despite machine learning algorithms offering a more robus...
Kidney pathology of immunoglobulin A nephropathy (IgAN), which is the key finding of both diagnosis and risk stratification, involves labor-intensive manual interpretation as well as unavoidable interpreter-dependent variabilities. We propose artific...
Explainable AI has garnered significant traction in science communication research. Prior empirical studies have firmly established that explainable AI communication could improve trust in AI and that trust in AI engineers was argued to be an under-e...
To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its pote...
The rapid expansion of online education has intensified the need to investigate the multifactorial determinants of university students' satisfaction with digital learning platforms. While prior studies have often examined technical or pedagogical com...
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