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HomeAi in HealthcareEnhancing Kidney Care with Machine Learning Models for Dynamic and Accurate Results

Enhancing Kidney Care with Machine Learning Models for Dynamic and Accurate Results

Artificial intelligence (AI) and deep and machine learning can be integrated into various areas of nephrology, as explained by Azra Bihorac, MD, MS, FCCM, FASN, during her presentation at the American Society of Nephrology’s (ASN) 2023 Kidney Week Annual Meeting. Bihorac emphasized the importance of AI literacy for healthcare professionals, stating that it is essential to dominate the conversation and not rely on others for this evolution.

Bihorac specifically mentioned the benefits of supervised machine learning, which can train data and algorithms to classify and label data and predict outcomes based on trends. She highlighted its usefulness in the perioperative surgical setting for assessing risk and identifying complications in real time.

Supervised machine learning is a type of AI and machine learning that can train data and algorithms to classify and label data to predict outcomes based on trends in the data. Image Credit: © nobeastsofierce –

On the other hand, deep learning is more suitable for larger data sets and utilizing dense data in a time series framework. Bihorac discussed its applications in the surgery setting, such as interpreting data, augmenting risk prediction, and delivering data to healthcare professionals through a network/cloud.

Bihorac outlined several capabilities that AI could have in kidney care, including improving organ function assessment, developing diagnostic tests beyond traditional measures like creatinine or urine, and enabling autonomous patient monitoring. AI can also aid pharmacists in better monitoring patients and informing drug use.

However, Bihorac warned about the biases that AI models, including large language models (LLM), may carry, as they learn and grow from the biases present in their training data. She emphasized the importance of explainable, dynamic, precise, autonomous, fair, and reproducible algorithms for optimized deep learning models and equitable healthcare.

In conclusion, Bihorac stressed the need for healthcare professionals to embrace the power of AI and deep learning models in personalized medicine. She stated that as the world moves towards using foundational AI models, healthcare professionals must actively participate in this transformation.


Biharoc A. Beyond AKI: How is AI Improving Critical Care in Illness? Session. ASN Kidney Week Annual Meeting. November 2 to 5, 2023. Philadelphia, PA.

Leah Sirama
Leah Sirama
Leah Sirama, a lifelong enthusiast of Artificial Intelligence, has been exploring technology and the digital realm since childhood. Known for his creative thinking, he's dedicated to improving AI experiences for all, making him a respected figure in the field. His passion, curiosity, and creativity drive advancements in the AI world.


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