(1). Multimodal Perception and Reasoning Ability
Medical data often involves various types: text (electronic medical records), images (CT, MRI), physiological indicators (heart rate, blood pressure), gene sequences, etc.
Agentic AI possesses multimodal perception capabilities, enabling it to understand complex environments and multiple data inputs, automatically extracting valuable information to provide doctors with more comprehensive diagnostic bases.
(2). Vast Medical Knowledge Base
Based on LLM, Agentic AI inherently possesses a vast amount of medical knowledge (covering basic medical knowledge, professional literature, clinical guidelines, drug databases, diagnostic and treatment methods, physiology, anatomy, pharmacology, and disease management), and can quickly provide personalized recommendations through its powerful reasoning capabilities. For example, based on patient symptoms and the latest clinical research, it can rapidly suggest treatment plans.
(3). Rapid Iteration and Update of Medical Knowledge
Agentic AI can autonomously learn and continuously update its knowledge base, timely associating new discoveries or technical guidelines in the medical field, thereby improving the accuracy and reliability of its diagnoses and providing higher quality medical services for patients.
(4). Autonomous Decision-Making and Planning Execution
Agentic AI can autonomously decompose complex medical tasks into multiple achievable sub-tasks, achieving efficient planning and execution through a “thinking chain.” Upon receiving a goal, it can autonomously plan actions and execute them step-by-step. For instance, when formulating treatment plans, Agentic AI can analyze patients’ historical data and genetic information to derive the most suitable treatment plan for the patient, and quickly make decisions based on the patient’s real-time health status and medical needs, such as adjusting medication dosages or recommending further examinations.
(5). Large-Scale Personalized Service Capability
Agentic AI supports dynamic recording of patient information through a memory module, facilitating continuous optimization of health management plans. It can provide personalized services based on long-term health data (such as medical history, lifestyle habits, genetic information), including health monitoring and prevention advice.
High-quality medical resources are primarily concentrated in a few large cities and major hospitals, while grassroots hospitals and rural areas have relatively scarce medical resources and lower service levels. This uneven distribution makes it difficult for patients in some areas to access high-quality medical services. For example, there are approximately 4.6 practicing physicians per thousand people in cities, while there are only about 2.2 in rural areas (data source: National Health Commission, 2021), more than double the difference.
Agentic AI can realize digital human doctors or act as virtual doctor assistants, allowing patients to receive quasi-expert diagnosis and treatment advice at home or in community grassroots medical institutions. This helps break geographical barriers, extending high-quality medical resources to grassroots medical institutions and achieving shared and optimized allocation of medical resources.
(2) Rapidly Growing Medical Demand Difficult to Meet
In 2023, the total number of diagnoses and treatments in national healthcare institutions reached 9.55 billion. With the aging population and increasing health awareness among residents, the demand for medical services continues to grow. This places higher demands on medical resources, requiring more medical facilities, equipment, and personnel to meet patient needs, and urgently needing to improve the efficiency of medical resource utilization. By the end of 2023, the elderly population aged 60 and above in China reached 296.97 million, accounting for 21.1% of the total population, among which those aged 65 and above accounted for 15.4% of the total population. It is expected that by 2025, the elderly population in China will increase to 300 million.
Agentic AI can effectively enhance the efficiency of medical services, such as automatically generating and filling electronic medical records, performing voice recognition and natural language processing on doctor-patient communication content, generating detailed medical records and categorizing them for storage, reducing the time doctors spend filling out records, improving record quality, and lowering the risk of human error. It can also assist doctors in analyzing medical images, such as CT and MRI, providing preliminary diagnostic suggestions, alleviating the burden on radiologists, and improving diagnostic efficiency and accuracy.
(3) High Investment, Long Cycle, and Low Success Rate in New Drug Development
New drug development from preclinical research to final market launch involves multiple stages including drug discovery, non-clinical research, clinical research, drug approval, and market launch. The average cycle takes at least 10 years and can take several decades, with total R&D costs generally exceeding 10 billion RMB. Moreover, the success rate of new drug development is very low, with less than 8% of R&D outcomes transitioning from clinical phase I to market approval.
Agentic AI can process and analyze vast amounts of medical literature, genetic and drug reaction data, discovering potential drug targets and treatment plans, accelerating the drug development process. With Agentic AI’s intelligent decision support, researchers can more accurately select drug candidates, optimize drug structures, and enhance drug efficacy and safety.
Agentic AI can reshape the workflow of drug development, facilitating the pharmaceutical industry to enter a new stage driven by data, empowered by artificial intelligence, and highly automated.
(4) Slow Promotion of New Medical Achievements
Medical research is rapidly advancing, especially in many interdisciplinary studies, making it difficult for doctors to quickly and fully understand the latest medical research findings and grasp the latest knowledge. The time from the birth of new medical achievements to grassroots hospital doctors mastering them can take several months or even years.
Agentic AI inherently possesses the ability to quickly organize, summarize, and retrieve professional literature content, and can automatically extract relevant content to generate easily understandable information outputs based on requirements.
(5) Insufficient Effectiveness in Public Health Prevention and Control
The key to epidemic monitoring and prevention lies in timely detection, which requires real-time processing of multi-source data (such as environmental monitoring, patient medical records, and population distribution) to quickly identify disease transmission trends and issue warnings.
Agentic AI can simulate and predict epidemic transmission patterns and prevention effects based on vast amounts of data, providing decision-makers with scientific and reasonable decision-making bases, thereby effectively enhancing the specificity and effectiveness of epidemic prevention and control.
(6) High Costs of Personalized Medicine
Patients’ conditions are complex and diverse, requiring comprehensive consideration of patients’ genetics, medical history, and lifestyle habits to generate highly personalized health management plans, necessitating long-term tracking of patients’ health status and dynamic adjustments of plans.
Agentic AI can integrate electronic health records (EHR), genetic data, and lifestyle data to provide patients with cost-effective personalized plans.
(1) In terms of healthcare service efficiency
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Intelligent Triage: Based on patient symptoms and health records, AI optimizes the registration and triage process, reducing patient waiting times.
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Intelligent Imaging Diagnosis: Quickly analyzes medical images (such as CT, MRI, X-rays) with AI, improving diagnostic efficiency and relieving the burden on doctors.
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Virtual Health Assistant: Provides health consultations, preliminary symptom analysis, and medical advice through chat and voice interaction.
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Intelligent Analysis of Electronic Health Records (EHR): Automatically mines and analyzes patient data to provide decision support for doctors.
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Intelligent Organization of Medical Records: Automatically extracts and summarizes important information, enhancing medical document management efficiency.
(2) In terms of new drug development
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Drug Discovery: Can be used for molecular structure analysis and new drug target discovery, simulating the binding of compounds to targets, screening high-potential lead molecules, and accelerating drug development.
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Drug Toxicity Assessment: Combines compound structures with known toxicity data to predict potential side effects of candidate compounds, reducing unnecessary animal testing.
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Preclinical Research: Automatically processes experimental data, discovering hidden trends or associations, assisting in judging the biological effects of drugs.
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Personalized Clinical Trial Plans: Recommends personalized dosing plans based on patients’ genotypes and metabolic characteristics, improving efficacy and reducing side effects.
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Drug Vigilance and Risk Assessment: Mines rare adverse events from medical reports, social media, and patient feedback, conducting risk analysis and issuing warnings.
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Clinical Trial Recruitment Platform: Smartly analyzes patient data to help match suitable volunteers for trials.
(3) In terms of health management and chronic disease prevention
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Intelligent Health Monitoring: Real-time monitoring of heart rate, blood pressure, blood sugar, etc., combined with wearable devices, providing timely alerts for abnormalities.
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Chronic Disease Management Services: Provides timely and valuable health guidance and medication reminders for patients with chronic diseases such as hypertension and diabetes based on personal medical history and health status.
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Health Lifestyle Assistant: Analyzes personal data autonomously, providing comprehensive optimization advice on diet, exercise, and sleep, proactively identifying health risks and providing solutions.
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Chronic Disease Prediction and Risk Assessment: Provides personalized predictions and risk assessments based on patients’ genetic data, medical history, and lifestyle habits.
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Intelligent Follow-Up: Regularly follows up with target patients to understand changes in their conditions, assisting doctors in efficiently collecting and analyzing patient situations and providing targeted treatment suggestions.
(4) In terms of promoting new medical achievements
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Intelligent Research Assistant for Doctors: Provides real-time updates on the latest medical literature, guidelines, and research findings, generating personalized learning plans.
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Intelligent Q&A for Medical Knowledge: Quickly and accurately answers professional questions from doctors and medical students based on vast medical knowledge, promoting the dissemination of medical knowledge.
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Clinical Pathway Optimization Tool: Helps doctors design the best treatment plans based on the latest research results.
(5) In terms of public health prevention and control
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Infectious Disease Monitoring and Early Warning: Analyzes multi-source data (hospital reports, social media, weather data, etc.) in real-time, predicting epidemic outbreaks and sending warnings.
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Digital Health Record Management: Smartly summarizes individual health records, providing comprehensive support for regional health management.
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Vaccination Optimization Platform: Develops the best vaccination strategies based on population characteristics, reducing disease transmission.
(6) Health Support for an Aging Society
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Health Companion Assistant for the Elderly: Provides warm and emotional daily companionship, life reminders, health monitoring, and emergency rescue services.
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Support Tools for Cognitive Impairment Patients: Assists Alzheimer’s patients in memory training and daily task management.
(7) Health Education and Psychological Support
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Mental Health Consultation Platform: Provides mental health advice through emotion recognition and voice analysis.
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Family Health Education Assistant: Helps family members understand the prevention and treatment of common diseases.
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Virtual Coach for Disease Rehabilitation: Provides guidance and psychological support for postoperative rehabilitation training.