Bacillus Calmette–Guérin (BCG) immunotherapy has been a cornerstone treatment for non-muscle-invasive bladder cancer for decades and still faces challenges, such as severe immune adverse reactions, which reduce its use as a first-line treatment. This review examines BCG therapy’s history, mechanisms, and current status, highlighting how nanotechnology and bioengineering are revitalizing its application. We discuss novel nanocarrier systems aimed at enhancing BCG’s efficacy while mitigating specific side effects. These approaches promise improved tumor targeting, better drug loading, and an enhanced stimulation of anti-tumor immune responses. Key strategies involve using materials such as liposomes, polymers, and magnetic particles to encapsulate BCG or functional BCG cell wall components. Additionally, co-delivering BCG with chemotherapeutics enhances drug targeting and tumor-killing effects while reducing drug toxicity, with some studies even achieving synergistic effects. While most studies remain experimental, this research direction offers hope for overcoming BCG’s limitations and advancing bladder cancer immunotherapy. Further elucidation of BCG’s mechanisms and rigorous safety evaluations of new delivery systems will be crucial for translating these innovations into clinical practice.

Bladder cancer (BC) is the tenth most common malignancy globally. Urothelial carcinoma (UC) is a major type of BC, and advanced UC (aUC) is associated with poor clinical outcomes and limited survival rates. Current options for aUC treatment mainly include chemotherapy and immunotherapy. These options have moderate efficacy and modest impact on overall survival and thus highlight the need for novel therapeutic approaches. aUC patients harbor a high tumor mutation burden and abundant molecular alterations, which are the basis for targeted therapies. Erdafitinib is currently the only Food and Drug Administration (FDA)-approved targeted therapy for aUC. Many potential targeted therapeutics aiming at other molecular alterations are under investigation. This review summarizes the current understanding of molecular alterations associated with aUC targeted therapy. It also comprehensively discusses the related interventions for treatment in clinical research and the potential of using novel targeted drugs in combination therapy.

Bacillus Calmette-Guérin (BCG) immunotherapy has been a cornerstone treatment for non-muscle invasive bladder cancer for decades and still faces challenges, such as severe immune adverse reactions, which reduce its use as a first-line treatment. This review examines BCG therapy’s history, mechanisms, and current status, highlighting how nanotechnology and bioengineering are revitalizing its application. We discuss novel nanocarrier systems aimed at enhancing BCG's efficacy while mitigating specific side effects. These approaches promise improved tumor targeting, better drug loading, and enhanced stimulation of anti-tumor immune responses. Key strategies involve using functional BCG cell wall components and co-delivering BCG with chemotherapeutics to achieve synergistic effects. While most studies remain experimental, this research direction offers hope for overcoming BCG's limitations and advancing bladder cancer immunotherapy. Further elucidation of BCG's mechanisms and rigorous safety evaluations of new delivery systems will be crucial for translating these innovations into clinical practice.

Background: Artificial intelligence (AI) is already showing enormous potential in the healthcare sector. Generative AI, particularly, is accelerating the sector's digital transformation by delivering intelligent decision support, automated diagnosis, and optimized resource allocation. DeepSeek‐R1, a large‐language model with a strong performance‐to‐cost ratio, has gained popularity as a foundation model in Chinese hospitals. However, the deployment of generative AI remains challenging, and hospitals continue to lack clear guidance on how to select among deployment architectures and how to balance computational demand with cost. Deeper, data‐driven analysis is therefore warranted to inform future roll‐outs. Methods: This study surveyed AI deployment across Chinese hospitals, with a focus on DeepSeek's potential applications under national policies. Data were collected from the top 20 hospitals, regional centers, and township hospitals via official WeChat platforms. The survey examined deployment strategies, model versions, and platform choices, while keeping in account hospital needs, data resources, and technological‐economic decisions. Results: The study highlights DeepSeek's impact on diagnostic accuracy, personalized treatment, medical documentation automation, and resource management optimization. Among the 17 surveyed hospitals, 6 hospitals employed detailed model versions, 5 used the 671B model, and 1 used the 32B version. Among 10 hospitals of different levels, 2 selected the 671B, 3 selected the 70B, and 4 selected the 32B model. All hospitals preferred local deployment. Different needs and applications were observed across the studied hospitals. Conclusions: Selection of the right AI model requires balancing computational power with cost. Larger models offer higher accuracy, but incur higher costs, whereas distilled models suit smaller hospitals with fewer resources. Future development should therefore focus on selecting deployment strategies based on the hospital size while addressing data quality disparities to bridge the regional healthcare gaps. As such, coordination among government, hospitals, and doctors is crucial for supporting smarter healthcare transitions.