AI Revolutionizes Diabetes Care: Personalized Treatment and Early Detection on the Horizon

AI for Diabetes Management: Personalized Care and Early Detection. | Newswise

The global incidence and prevalence of diabetes continue to rise, increasing rates of associated disability and mortality while imposing a substantial economic burden. Despite advancements in medical technology, diabetes management faces persistent challenges, including a shortage of specialists, uneven distribution of healthcare resources, and low patient adherence, all contributing to suboptimal glycemic control. A new review (doi: https://doi.org/10.1016/j.hcr.2024.100006) published in the journal Healthcare and Rehabilitation reveals how artificial intelligence (AI) is brining major changes to diabetes care. By analyzing data from blood sugar levels, medical history, and even retinal scans, AI tools can now predict diabetes subtypes, identify high-risk patients, and tailor solutions to individual needs -- improving accuracy, reducing healthcare costs and addressing critical gaps in diagnosis, treatment, and daily management. "AI isn't just a tool; it's a partner in care," explains the principal investigator of the study Dr. Ling Gao at the Central Laboratory at Shandong Provincial Hospital. "For example, AI can detect early signs of eye damage from diabetes in retinal images as accurately as specialists, which is critical for preventing blindness." The research highlights several breakthroughs: - Early Complication Detection: AI predicts risks like kidney disease and heart issues by spotting patterns humans might miss. - Personalized Treatment: Smart systems adjust insulin doses in real time, cutting dangerous blood sugar swings. - Diet and Exercise Guidance: Apps analyze meals via photos and suggest recipes, while AI coaches recommend workouts based on location and health data. Notably, AI even outperformed traditional methods in some areas. "For instance, CT scans analyzed by AI could screen for osteoporosis in diabetes patients as effectively as specialized bone density tests," adds Gao. "Wearable devices like smart glucose monitors and socks that detect foot infections further showcase AI's potential to keep patients healthy at home." However, challenges remain. "AI models need diverse data to avoid biases," emphasizes senior author Dr. Zhongming Wu, a professor in basic and translational studies of endocrine and metabolic diseases, at Affiliated Hospital of Endocrinology and Metabolism, Shandong First Medical University. "A tool trained based on just one population might fail elsewhere." Additionally, issues like data privacy and the "black box" nature of some AI decisions require careful handling. The study calls for stronger collaboration between tech developers, doctors, and policymakers to ensure AI tools are safe, fair, and accessible. "AI is a powerful ally in diabetes care, but human oversight remains essential," notes Gao. "While AI won't replace human clinicians, it empowers them to make faster, smarter decisions -- ultimately transforming diabetes from a one-size-fits-all disease into a condition managed with precision and foresight." This study was supported by the National Natural Science Foundation of China (Grant No. 82370788). About Healthcare and Rehabilitation Healthcare and Rehabilitation is a peer-reviewed, Open Access journal for reporting original contributions that enable progress in multidisciplinary healthcare and rehabilitation. The journal is dedicated to publishing high-quality papers covering various disciplines related to healthcare and rehabilitation, including but not limited to Rehabilitation Medicine, Public Health and Preventive Medicine, Nursing, Clinical Medicine, Pharmacology, Psychology, Integrated Traditional Chinese and Western Medicine, Biomedical Engineering, Materials Science and Engineering, Information Science, Artificial Intelligence and other related disciplines.

Review: Artificial intelligence is shaping the future of diabetes care

KeAi CommunicationsFeb 26 2025 The global incidence and prevalence of diabetes continue to rise, increasing rates of associated disability and mortality while imposing a substantial economic burden. Despite advancements in medical technology, diabetes management faces persistent challenges, including a shortage of specialists, uneven distribution of healthcare resources, and low patient adherence, all contributing to suboptimal glycemic control. A new review (doi: https://doi.org/10.1016/j.hcr.2024.100006) published in the journal Healthcare and Rehabilitation reveals how artificial intelligence (AI) is bringing major changes to diabetes care. By analyzing data from blood sugar levels, medical history, and even retinal scans, AI tools can now predict diabetes subtypes, identify high-risk patients, and tailor solutions to individual needs -- improving accuracy, reducing healthcare costs and addressing critical gaps in diagnosis, treatment, and daily management. AI isn't just a tool; it's a partner in care. For example, AI can detect early signs of eye damage from diabetes in retinal images as accurately as specialists, which is critical for preventing blindness." Dr. Ling Gao, principal investigator of the study, Central Laboratory at Shandong Provincial Hospital The research highlights several breakthroughs: - Early Complication Detection: AI predicts risks like kidney disease and heart issues by spotting patterns humans might miss. - Personalized Treatment: Smart systems adjust insulin doses in real time, cutting dangerous blood sugar swings. - Diet and Exercise Guidance: Apps analyze meals via photos and suggest recipes, while AI coaches recommend workouts based on location and health data. Notably, AI even outperformed traditional methods in some areas. "For instance, CT scans analyzed by AI could screen for osteoporosis in diabetes patients as effectively as specialized bone density tests," adds Gao. "Wearable devices like smart glucose monitors and socks that detect foot infections further showcase AI's potential to keep patients healthy at home." However, challenges remain. "AI models need diverse data to avoid biases," emphasizes senior author Dr. Zhongming Wu, a professor in basic and translational studies of endocrine and metabolic diseases, at Affiliated Hospital of Endocrinology and Metabolism, Shandong First Medical University. "A tool trained based on just one population might fail elsewhere." Additionally, issues like data privacy and the "black box" nature of some AI decisions require careful handling. The study calls for stronger collaboration between tech developers, doctors, and policymakers to ensure AI tools are safe, fair, and accessible. "AI is a powerful ally in diabetes care, but human oversight remains essential," notes Gao. "While AI won't replace human clinicians, it empowers them to make faster, smarter decisions -- ultimately transforming diabetes from a one-size-fits-all disease into a condition managed with precision and foresight." KeAi Communications Journal reference: Ma, S., et al. (2025). Artificial intelligence and medical-engineering integration in diabetes management: Advances, opportunities, and challenges. Healthcare and Rehabilitation. doi.org/10.1016/j.hcr.2024.100006.