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Development of Artificial Intelligence Systems for Chronic Kidney Disease
1Department of Health Data Science, Kawasaki Medical School, Kukrashiki, Japan.
Insights
Artificial intelligence (AI) systems can now predict chronic kidney disease (CKD) progression, dialysis timing, and patient death. These AI tools, including natural language processing (NLP), also aid in clinical guideline creation, improving efficiency and potentially patient outcomes.
Area of Science:
- Nephrology
- Artificial Intelligence
- Data Science
Background:
- Chronic kidney disease (CKD) is a growing global health concern, linked to cardiovascular disease and reduced life expectancy.
- Increasing prevalence in Japan necessitates accurate prognosis prediction for effective treatment and risk stratification.
- Advancements in data science have enabled the construction of large CKD databases, facilitating deeper understanding of the disease.
Purpose of the Study:
- To develop an artificial intelligence (AI) system for accurate prognosis prediction in chronic kidney disease (CKD) patients.
- To create a clinical practice guideline support system (Doctor K) utilizing natural language processing (NLP) to enhance efficiency.
- To validate the AI system's ability to reflect CKD pathology and predict patient prognosis.
Main Methods:
- Development of an AI system for predicting CKD progression, dialysis initiation, and mortality.
- Implementation of a natural language processing (NLP) AI system (Doctor K) to support clinical guideline creation.
- Analysis of medical word virtual space using category theory on big patient data to validate AI's reflection of CKD pathology.
Main Results:
- An AI-powered prognosis prediction system for CKD patients was developed and made publicly available online.
- The Doctor K NLP AI system significantly improved efficiency in preparing clinical practice guidelines for the Japanese Society of Nephrology.
- Mathematical analysis confirmed that the NLP AI system's medical word virtual space accurately reflects CKD pathology, suggesting predictive capabilities.
Conclusions:
- AI systems show promise in accurately predicting the prognosis of chronic kidney disease (CKD), including progression and mortality.
- AI, particularly NLP, can substantially improve the efficiency of clinical guideline development.
- The application of AI and big data in nephrology holds potential for discovering novel treatments and enhancing patient outcomes.
Abstract:
Chronic kidney disease (CKD) is a complex disease that is related not only to dialysis but also to the onset of cardiovascular disease and life prognosis. As renal function declines with age and depending on lifestyle, the number of patients with CKD is rapidly increasing in Japan. Accurate prognosis prediction for patients with CKD in clinical settings is important for selecting treatment methods and screening patients with high-risk. In recent years, big databases on CKD and dialysis have been constructed through the use of data science technology, and the pathology of CKD is being elucidated. Therefore, we developed an artificial intelligence (AI) system that can accurately predict the prognosis of CKD such as its progression, the timing of dialysis introduction, and death. Aiming for its social implementation, the prognosis prediction system developed for patients with CKD was released on the website. We then developed a clinical practice guideline creation support system called Doctor K as an AI system. When creating clinical practice guidelines, huge amounts of manpower and time are required to conduct a systematic review of thousands of papers. Therefore, we developed a natural language processing (NLP) AI system to significantly improve work efficiency. Doctor K was used in the preparation of the guidelines of the Japanese Society of Nephrology. Furthermore, by comparing and analyzing the medical word virtual space constructed by the NLP AI system based on patient big data, we proved using the latest mathematical theory (category theory) that this system reflects the pathology of CKD. This suggests the possibility that the NLP AI system can predict patient prognosis. We hope that, through these studies, the use of AI based on big data will lead to the development of new treatments and improvement in patient prognosis.
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