Dommeti Hemalatha,
Adapa Gowri Shankar,
Kakileti Rajesh,
Iragavarapu Sravan Bharadwaj,
Gidla Sudheer Babu,
- UG Scholar, Department of Engineering, Bonam Venkata Chalamayya Engineering College (Autonomous), Odalarevu, Andhra Pradesh, India
- UG Scholar, Department of Engineering, Bonam Venkata Chalamayya Engineering College (Autonomous), Odalarevu, Andhra Pradesh, India
- UG Scholar, Department of Engineering, Bonam Venkata Chalamayya Engineering College (Autonomous), Odalarevu, Andhra Pradesh, India
- UG Scholar, Department of Engineering, Bonam Venkata Chalamayya Engineering College (Autonomous), Odalarevu, Andhra Pradesh, India
- Assistant Professor, Department of Engineering, Bonam Venkata Chalamayya Engineering College (Autonomous), Odalarevu, Andhra Pradesh, India
Abstract
The Automated Healthcare Support System with Artificial Intelligence (AI) presents a smart and scalable digital solution aimed at improving the accessibility and efficiency of healthcare services. The system is designed to provide preliminary medical guidance, perform symptom-based analysis, and deliver health-related insights through an intuitive user interface. By enabling early identification of potential health conditions, it assists users in determining the necessity of professional medical consultation. The proposed platform utilizes advanced computational models to interpret user-reported symptoms and generate probable health assessments. It offers non-prescriptive outputs such as precautionary measures, wellness suggestions, and general guidance to promote informed decision-making. In addition, the system incorporates an adaptive learning mechanism that enhances its analytical performance over time using updated datasets and user interaction patterns. To improve user engagement and accessibility, the system supports multilingual interaction and personalized recommendations based on individual health profiles. It also integrates continuous monitoring capabilities through wearable device compatibility and generates alerts for unusual health patterns, facilitating proactive healthcare management. The platform further includes essential functionalities such as digital health record management, automated appointment scheduling, and real-time assistance. Its modular and scalable architecture allows seamless integration with existing healthcare infrastructures, ensuring flexibility and future expansion. This system is particularly beneficial for individuals in remote and underserved regions, where access to medical resources is limited. By supporting early-stage detection and continuous health tracking, the proposed AI-based solution contributes to improved healthcare outcomes and reduced burden on medical professionals. Overall, the system represents an efficient and intelligent approach toward modernizing healthcare delivery and promoting accessible digital health services. Instead of providing direct prescriptions, the system offers precautionary measures, general health recommendations, and guidance on whether professional care is required. The system is designed with a scalable architecture, allowing integration with existing healthcare infrastructures. It is particularly useful for individuals in remote regions where access to healthcare services is limited. Overall, the proposed approach demonstrates how AI can contribute to efficient, accessible, and proactive healthcare delivery.
Keywords: Artificial Intelligence, Healthcare Assistant, Machine Learning, Natural Language Processing, Symptom Evaluation, Telemedicine, Digital Healthcare
[This article belongs to Research and Reviews : A Journal of Medical Science and Technology ]
Dommeti Hemalatha, Adapa Gowri Shankar, Kakileti Rajesh, Iragavarapu Sravan Bharadwaj, Gidla Sudheer Babu. Automated Healthcare Support System with AI. Research and Reviews : A Journal of Medical Science and Technology. 2026; 15(01):-.
Dommeti Hemalatha, Adapa Gowri Shankar, Kakileti Rajesh, Iragavarapu Sravan Bharadwaj, Gidla Sudheer Babu. Automated Healthcare Support System with AI. Research and Reviews : A Journal of Medical Science and Technology. 2026; 15(01):-. Available from: https://journals.stmjournals.com/rrjomst/article=2026/view=242274
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| Volume | 15 |
| Issue | 01 |
| Received | 28/04/2026 |
| Accepted | 30/04/2026 |
| Published | 30/04/2026 |
| Publication Time | 2 Days |
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