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Abstract Virtual staining technology offers a promising solution to overcome the time-consuming and sample-consumption nature of conventional histochemical staining in breast cancer pathology. This study presents a novel...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

Abstract Graph Neural Networks have emerged as a powerful paradigm for artificial intelligence driven drug discovery, offering molecular representation learning that surpasses many conventional approaches. Traditional ex...

Abstract A prompt and precise diagnosis is necessary to lessen the worldwide burden of asthma, a common chronic respiratory condition. Spirometry is one of the resource-intensive conventional methods that frequently misc...

Abstract With the increasing performance requirements for data acquisition in applications such as the Internet of things and artificial intelligence, analog-to-digital converters (ADCs) face stringent trade-offs among s...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Abstract Machine-generated music (MGM) has become a groundbreaking innovation with wide-ranging applications, such as music therapy, personalised editing, and creative inspiration within the music industry. However, the ...

Abstract Cardiovascular disease remains the leading cause of death and disability worldwide. The convergence of big data and artificial intelligence (AI) is reshaping precision cardiovascular medicine through multimodal ...

Abstract Fractures are among the most common presentations to emergency and orthopedic services, yet radiograph interpretation remains inconsistent, particularly in resource-limited and off-hours settings. Weakly supervi...