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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 Underwater imaging suffers from various challenges such as color distortion, low contrast, and reduced visibility caused by light attenuation. Addressing these issues is crucial for improving the performance of ...

Abstract In the world of the Internet of Things (IoT), wireless sensor networks (WSNs) play a vital role in enabling seamless communication between connected devices. In a WSN data prediction system based, clustering and...

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 Timely and accurate detection of COVID-19 is essential for rapid intervention and preventing the spread of the disease, especially among vulnerable populations. This study introduces a new two-stage methodology ...

Abstract To address the limitations of existing oil-well production forecasting models, particularly suboptimal hyperparameter selection, difficulties in fine-tuning, insufficient global search capability, and slow conve...

Abstract In response to the problems of large fluctuations in electricity prices and difficulty in long-term forecasting caused by the large-scale integration of new energy in the electricity market, this paper construct...

Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Abstract Air pollution, particularly Nitrogen Dioxide ( $$\text {NO}_2$$ ) and ground-level ozone ( $$\text {O}_3$$ ), poses major risks to human health and the environment, making accurate forecasting essential for effe...