Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
OBJECTIVE: Assess whether a single instance-segmentation model can operate robustly across multiple cytological stains, avoiding stain-specific pipelines without sacrificing accuracy. METHODS: We consolidated three expert-annotated datasets (Papanicolaou, Feulgen, AgNOR), standardised their formats and trained Mask R-CNN, Mask2Former, YOLO11n and YOLO12n under two regimes: per-stain and unified mu...
BACKGROUND: Artificial intelligence (AI) is rapidly integrating into the nursing field, evolving from simple assistive tools to complex applications that transform nursing practice models, thereby profoundly impacting the professional jurisdiction of nurses. Given the lack of systematic theoretical integration in existing research, this study employs Abbott's Jurisdictional Framework and uses meta...
Oil spills pose serious environmental risks, hence accurate and rapid detection is critical for marine monitoring. Synthetic Aperture Radar (SAR) imag...
Forced alignment is a common tool to align audio with orthographic and phonetic transcriptions. Most forced alignment tools provide only point-estimat...
INTRODUCTION: This study aimed to evaluate the effectiveness of a generative artificial intelligence based simulated patient model in improving gyneco...
The growing use of artificial intelligence (AI) in medicine has highlighted the imperative for privacy-preserving and high-accuracy diagnostic systems...
The RNA inverse folding problem aims to identify nucleotide sequences that preferentially adopt a given target secondary structure. While various heur...
Pharmacy preceptors are central to experiential learning, yet there is a lack of guidance on how to integrate generative artificial intelligence (GenA...
BACKGROUND: Depression is a pervasive global mental health issue, yet access to trained professionals remains severely limited. With the rapid advance...
In this article, we investigate the task optimization for fixed-time control of intermittent human-robot interaction, where a human operator assists t...
BACKGROUND: Artificial intelligence (AI) is increasingly applied in dentistry to enhance diagnosis and treatment planning. Its integration raises ethi...
In many real-world applications, binary and multi-class classification problems involving imbalanced data and overlapping boundaries present a signifi...
Topological phases, as characterized by their topological invariants, have been considered as distinct states from the raw phases and hold great promi...
Accurate segmentation of the Clinical Target Volume (CTV) and Organs At Risk (OARs) is a prerequisite for effective cervical cancer radiotherapy. Howe...
Neural networks have promise as surrogate partial differential equation (PDE) solvers, but it remains a challenge to use these concepts to solve probl...
BACKGROUND: Generative artificial intelligence (GenAI) is rapidly expanding in higher education and clinical practice. However, its use during clinica...
BACKGROUND AND OBJECTIVE: With the rapid growth of internet technologies, the transmission and storage of multimedia data have become increasingly con...
The accurate extraction of grain boundaries from metallographic images is a prerequisite for quantitative microstructural analysis, but it is often hi...
Accurate fine-grained classification of ovarian tumors from ultrasound images remains challenging due to speckle noise, boundary ambiguity, structural...
The clinical translation of bone tissue engineering is constrained by a severe multiscale design trade-off: the requirement for load-bearing mechanica...