A transformative tool: AI redefines healthcare services in China
AI is proving to be transformative across medical domains by enhancing patient experiences and empowering healthcare providers.
TroibNews 
In Shenzhen, 57-year-old Li Hualiang, who suffers from hypertension and heart disease, was looking for dental implants but had concerns about his cardiac health. He sought help from Luohu People's Hospital, which has an artificial intelligence guidance system designed to simplify complex medical cases.
After detailing his symptoms, the system provided registration advice that helped Li easily schedule a cardiology appointment. When he entered the consultation room, the cardiology doctor's computer already had information about Li's condition displayed.
Following a brief inquiry, the AI system offered diagnostic suggestions in just eight seconds. To further address Li's concerns regarding dental implants, the doctor used the AI tool to evaluate risks and precautions related to the procedure.
Shenzhen, a leader in AI-driven healthcare innovation, has integrated 16 categories along with 63 scenarios and introduced nearly 450 AI products within various medical institutions.
Pei Xiaoyang, the director of cardiovascular medicine at Luohu People's Hospital, highlighted how AI assists in managing patients with multiple health issues. He noted, "Patients sometimes present with comorbidities, and specialists may lack expertise in overlapping disciplines. AI bridges these gaps by offering insights into medications and treatments beyond our core specialties, which is helpful for delivering precise care."
AI's potential to transform diagnosis and critical care is evident. In the past, pathologists spent considerable time manually screening lesion cells from normal ones under microscopes, exposing the process to fatigue-related misdiagnosis. To counter this, The First Affiliated Hospital of Zhejiang University School of Medicine developed an AI-powered pathological model. This model utilizes digital slide scanners to convert glass slides into digital images that are uploaded to the cloud for AI-assisted analysis.
The AI model efficiently filters out normal samples while flagging areas that may indicate lesions, significantly enhancing both efficiency and accuracy in diagnostics. It also alleviates the workload of younger pathologists, enabling them to focus on developing their skills.
In intensive care units, where medical devices produce vast amounts of data, doctors used to manually compile fragmented patient information for critical decision-making. Currently, the hospital's AI-driven ICU model organizes patient conditions into structured modules and creates digital simulations using real-time data from connected devices.
For instance, in the case of a heart-transplant patient on extracorporeal membrane oxygenation, an ICU doctor illustrated how the AI system replicates clinical reasoning. It analyzes trends in vital signs, lab results, and device metrics to help determine the best time for ECMO removal. Cai Hongbo, director of the Department of Critical Care Medicine at The First Affiliated Hospital of Zhejiang University School of Medicine, remarked, "AI acts as a powerful assistant to ICU teams. It continuously monitors patients for subtle changes and emerging risks, then analyzes and organizes data according to the clinical protocols we've programmed. This capability is transformative."
Having been in use for six months, the AI-driven ICU model has built a high-quality ICU database, demonstrated professional-grade assistance capabilities, reduced clinician workloads, and streamlined time-consuming tasks like information retrieval and decision-making.
AI is proving effective in diverse areas such as medical imaging, genomics, smart triage, chronic disease management, and drug research and development. It is improving patient experiences, supporting medical staff, and promoting efficient resource utilization, which makes high-quality care more accessible.
However, challenges persist. Balancing technological advancements with strong privacy protections, ensuring algorithmic fairness, and maintaining transparency in decision-making are pressing issues that need ongoing focus.
To address these concerns, regulatory bodies, including China's National Health Commission, are actively developing policies to encourage responsible AI development in healthcare. These initiatives aim to align innovation with standardization, paving the way for a future where both patients and healthcare professionals can enjoy safer and more efficient care.
Max Fischer for TROIB News
After detailing his symptoms, the system provided registration advice that helped Li easily schedule a cardiology appointment. When he entered the consultation room, the cardiology doctor's computer already had information about Li's condition displayed.
Following a brief inquiry, the AI system offered diagnostic suggestions in just eight seconds. To further address Li's concerns regarding dental implants, the doctor used the AI tool to evaluate risks and precautions related to the procedure.
Shenzhen, a leader in AI-driven healthcare innovation, has integrated 16 categories along with 63 scenarios and introduced nearly 450 AI products within various medical institutions.
Pei Xiaoyang, the director of cardiovascular medicine at Luohu People's Hospital, highlighted how AI assists in managing patients with multiple health issues. He noted, "Patients sometimes present with comorbidities, and specialists may lack expertise in overlapping disciplines. AI bridges these gaps by offering insights into medications and treatments beyond our core specialties, which is helpful for delivering precise care."
AI's potential to transform diagnosis and critical care is evident. In the past, pathologists spent considerable time manually screening lesion cells from normal ones under microscopes, exposing the process to fatigue-related misdiagnosis. To counter this, The First Affiliated Hospital of Zhejiang University School of Medicine developed an AI-powered pathological model. This model utilizes digital slide scanners to convert glass slides into digital images that are uploaded to the cloud for AI-assisted analysis.
The AI model efficiently filters out normal samples while flagging areas that may indicate lesions, significantly enhancing both efficiency and accuracy in diagnostics. It also alleviates the workload of younger pathologists, enabling them to focus on developing their skills.
In intensive care units, where medical devices produce vast amounts of data, doctors used to manually compile fragmented patient information for critical decision-making. Currently, the hospital's AI-driven ICU model organizes patient conditions into structured modules and creates digital simulations using real-time data from connected devices.
For instance, in the case of a heart-transplant patient on extracorporeal membrane oxygenation, an ICU doctor illustrated how the AI system replicates clinical reasoning. It analyzes trends in vital signs, lab results, and device metrics to help determine the best time for ECMO removal. Cai Hongbo, director of the Department of Critical Care Medicine at The First Affiliated Hospital of Zhejiang University School of Medicine, remarked, "AI acts as a powerful assistant to ICU teams. It continuously monitors patients for subtle changes and emerging risks, then analyzes and organizes data according to the clinical protocols we've programmed. This capability is transformative."
Having been in use for six months, the AI-driven ICU model has built a high-quality ICU database, demonstrated professional-grade assistance capabilities, reduced clinician workloads, and streamlined time-consuming tasks like information retrieval and decision-making.
AI is proving effective in diverse areas such as medical imaging, genomics, smart triage, chronic disease management, and drug research and development. It is improving patient experiences, supporting medical staff, and promoting efficient resource utilization, which makes high-quality care more accessible.
However, challenges persist. Balancing technological advancements with strong privacy protections, ensuring algorithmic fairness, and maintaining transparency in decision-making are pressing issues that need ongoing focus.
To address these concerns, regulatory bodies, including China's National Health Commission, are actively developing policies to encourage responsible AI development in healthcare. These initiatives aim to align innovation with standardization, paving the way for a future where both patients and healthcare professionals can enjoy safer and more efficient care.
Max Fischer for TROIB News
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