Page 26 - IMDR Journal 2025

Research Article
Predictive Healthcare & Monitoring with AI devices that incorporate AI-powered health tracking,
offering information on heart rate variability, blood sugar
Smartwatches and health bands do more than count steps
now. With AI, wearable devices can track heart rate, sugar trends, and levels of physical activity.
levels, and more in real time. This helps people manage AI Chatbots and Virtual Assistants for Diabetes Care
conditions like diabetes better and spot issues early. AI can AI-driven virtual assistants and chatbots are increasingly
also predict future health problems by looking at trends in used to support diabetic patients in daily disease
your health data. It gives doctors and patients a chance to act management and education. AI-powered platforms like
early — avoiding emergencies and hospital stays. IBM Watson and Ada Health provide personalized
AI in the Management and Prediction of Diabetes recommendations on diet, medications, and glucose
Personalized treatment suggestions, ongoing monitoring, monitoring. Chatbots offer 24/7 support, answering patient
and early risk assessment are the main goals of AI's queries, scheduling doctor appointments, and providing
application in diabetes care. The main AI-driven behavioural coaching for diabetes self-management.
advancements in diabetes care are described in depth in the Through predictive modelling, remote monitoring, and AI-
next subsections. assisted decision-making, AI enhances diabetes care by
reducing complications, improving glycemic control, and
Diabetes Risk Assessment Using Predictive Analytics
empowering patients with self-management tools.
To estimate a person's risk of Type 2 diabetes, AI-powered Case Studies and Real-World Implementations
machine learning algorithms examine a variety of
physiological data, lifestyle choices, medical history, and AI-driven technologies have already demonstrated
genetic variables. Supervised learning models leverage big significant success in managing Type 2 diabetes. Several
datasets from electronic health records (EHRs), patient real-world case studies highlight the effectiveness of AI-
surveys, and real-time monitoring devices to identify high- based models in predicting, monitoring, and treating
risk individuals. Neural networks and decision trees diabetes.
examine numerous risk indicators such as body mass index Google’s DeepMind AI for Diabetes Prediction
(BMI), fasting glucose levels, and physical activity patterns
DeepMind, a subsidiary of Google Health, developed AI-
to forecast disease development. According to studies, powered retinal imaging analysis to detect early signs of
artificial intelligence (AI) can forecast the start of diabetes diabetic retinopathy and macular edema—two major
years before a clinical diagnosis is made, enabling prompt complications of diabetes. The AI model demonstrated an
interventions and preventative actions. accuracy rate of over 94%, outperforming traditional
AI-Powered Customized Treatment Programs diagnostic methods.
AI's capacity to adapt treatment plans to the specific Customized Diabetes Management with IBM Watson
requirements of each patient is one of its main benefits in the Health
management of diabetes. Healthcare providers can benefit IBM Watson Health analyses patient data and offers
from AI-driven decision support systems (DSS) in the individualized diabetes care strategies using deep learning
following ways: and natural language processing (NLP).Watson's AI model
● Optimizing Insulin Therapy AI-powered insulin pumps has effectively helped doctors with dietary planning,
modify insulin dosage in real-time based on data from monitoring high-risk diabetic patients, and adjusting insulin
continuous glucose monitoring. dosages.
● Personalized Dietary and Exercise Plans AI algorithms AI-Powered Insulin Dosing Devices: The Mini Med
examine a patient's metabolism, activity levels, and food 670G from Med tronic
habits to provide the best diet and exercise plans. Medtronic developed the MiniMed 670G, the first hybrid
● Medication Adherence Monitoring AI-powered closed-loop insulin pump powered by AI and machine
smartphone apps keep tabs on patients' compliance with learning. The gadget automatically changes insulin delivery
their prescription regimens, reminding them when based on real-time glucose measurements, leading to
necessary and examining health trends to identify possible enhanced glycemic control and less hypoglycemia episodes.
dosage changes. AI-Powered Diabetes Management Platforms: Livongo
AI in Wearable Technology and Remote Monitoring| and My Sugr
AI-powered wearables have revolutionized diabetes care by Livongo Health is an AI-powered diabetes management
offering real-time glucose monitoring, trend analysis, and platform that gives diabetic patients coaching and real-time
early warning alerts. Continuous Glucose Monitors feedback based on lifestyle patterns and glucose levels. To
(CGMs): AI is used by devices like the Dexcom G6 and improve diabetic self-care, MySugr, an AI-powered
FreeStyle Libre to assess glucose variations and forecast smartphone app, combines meal logging, blood glucose
possible episodes of hypoglycemia or hyperglycemia. Smart monitoring, and AI-based risk assessments.
Insulin Pens: AI-enabled smart pens track insulin injection
patterns, dosage levels, and patient adherence, improving
self-management. AI-Powered Fitness Trackers and RESEARCH METHODOLOGY
Smartwatches: Fitbit and Apple Watch are two examples of
In order to assess the efficacy of AI in predictive healthcare

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