SU_231107_Diabetes_LEAD STORY1_web
Image Credit: Shutterstock


From personalised treatment plans to future innovation, experts delve deep into AI’s effects on diabetes management

In a world driven by technological innovation, Artificial Intelligence (AI) has emerged as a powerful ally in the ongoing battle against diabetes. From personalised treatment plans to predictive analytics, AI is revolutionising our approach to diabetes care.

Dr Ghaida Kaddaha, Consultant Endocrinologist at Medcare Women and Children Hospital, emphasises AI’s role in analysing data from CGM devices. She states, “AI algorithms can recognise patterns, anomalies and trends, enabling timely adjustments to insulin dosages and lifestyle choices.” This extends to identifying early indicators of blood sugar fluctuations that might go unnoticed, providing individuals with preventive actions.

Dr John Alexander. Consultant Endocrinologist, Aster Hospital Mankhool, highlights AI’s use of diverse data sets for predictions, including historical blood sugar readings, diet, exercise, and environmental factors. He mentions the recent FDA approval of an automated insulin delivery system, underlining how AI empowers healthcare providers to make informed decisions and engage patients in effective diabetes management.

Dr Mohamed Jamshid, Specialist Internal Medicine at LLH Hospital Abu Dhabi, likens AI to an intelligent assistant, constantly monitoring various aspects of daily life. He points out AI’s ability to make predictions based on lifestyle choices, providing a proactive heads-up to patients. Dr Jamshid emphasises the financial benefits, stating, “Better sugar control means fewer hospital visits and a reduced chance of serious problems, translating to significant savings on medical bills.”

Challenges and limitations

One central challenge in deploying AI for diabetes management is data quality and availability. Dr Ashwin Porwal, Specialist Internal Medicine at Medcare Medical Centres – Al Barsha and Meadows underscores the importance of trustworthy data for effective AI models. He mentions ongoing efforts to develop explainable AI techniques to enhance transparency and understanding.

While AI has shown effectiveness in managing gestational and pediatric diabetes, challenges persist in complex cases with comorbid conditions. Dr Porwal notes that AI struggles in scenarios requiring a multifaceted approach. Patient engagement and driving behavioural change remain challenges, as the human element is pivotal in fostering compliance and lifestyle modifications.

Dr Alexander outlines the need for large and diverse data sets for predicting glucose levels, addressing concerns about data privacy and security. He acknowledges the effectiveness of AI in certain patient groups, emphasizing continuous refinement and the anticipation of forthcoming regulations to ensure safe and ethical AI practices.

Dr Jamshid highlights privacy concerns and the tech divide, emphasising the need for educating patients and facilitating smooth AI integration with hospital systems. He recognises the emotional side of diabetes, noting AI’s ongoing learning curve in understanding human feelings.

SU_231107_Diabetes_LEAD STORY2_web
Image Credit: Shutterstock

Transformative role

AI plays a transformative role in personalising diabetes treatment plans, leveraging machine learning to analyse diverse data sources. Dr Abdul Jabbar Consultant Internal Medicine, Endocrinologist at Medcare Hospital Al Safa, emphasises AI’s strength in tailoring medication management, resulting in more effective and side-effect-minimised treatment regimens.

Real-time monitoring by AI systems allows immediate adjustments to treatment plans, reducing the risk of hyperglycemic or hypoglycemic events. Dr Jabbar underlines AI’s extension beyond medication to lifestyle recommendations, providing tailored guidance for enhanced glycemic control.

Dr Alexander says machine learning plays a vital role in the personalisation process by continuously learning from a patient’s data and adjusting treatment recommendations accordingly. For example, a patient with high BMI would benefit from newer drugs like GLP-1 analogues. “This would lead to better outcomes which include improved blood sugar control, delaying or predicting the onset of complications and improved quality of life with reduced treatment-related side effects,” says Dr Alexander.

Dr Jamshid agrees that AI really shines when it comes to personalisation. “The outcomes can be pretty impressive,” says Dr Jamshid. “I’ve seen patients who used to have roller coaster blood sugars now having more stable levels throughout the day. They feel better, have more energy, and they’re less stressed about managing their diabetes because they’ve got this AI system that’s helping them out.”

The real kicker is the long-term results, explains Dr Jamshid, as patients who have this kind of personalised care often see a reduction in the risk of complications. “We’re talking about the big stuff — heart problems, kidney issues, and eye damage that can come from diabetes.”

What the future holds

According to Dr Iryna Shatokhina, Specialist Endocrinologist at Medcare Women & Children Hospital, the future of AI-driven diabetes management holds great promise, with several exciting developments on the horizon. “As endocrinologists, we can expect more personalised treatment plans, continuous monitoring through wearable devices, improved predictive analytics, and enhanced telehealth services,” says Dr Shatokhina.

Shatokhina adds that AI algorithms will increasingly provide treatment recommendations tailored to individual patients, incorporating their unique health history, lifestyle, and real-time data. “To stay updated in this rapidly evolving field, healthcare professionals can attend relevant conferences, engage in online communities, collaborate with AI experts, and explore educational opportunities focused on AI in healthcare,” she says.

Dr Alexander envisions an exciting future with advanced AI models, greater accuracy in predicting blood sugar levels, and improved integration with wearable devices for real-time monitoring and feedback.

Dr Jamshid concludes that the future of AI in diabetes care is all about personalisation and prediction. “Think of AI as a health crystal ball that can foresee how your lifestyle choices will affect your blood sugar levels and help prevent complications before they happen,” he says.

“For healthcare pros, keeping up with AI’s rapid growth involves staying plugged into the latest research, attending webinars, and networking. It’s a fast-paced learning curve, but by staying informed and adaptable, we’re making sure we harness the best of AI for our patients.”