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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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| Paper Title: | A Study on Applications of Artificial Intelligence in Healthcare |
| Authors Name: | Sruthi , Vijayalakshmi E , Sabari Giri Vasan A |
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| Author Reg. ID: |
IJRTI_210050
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| Published Paper Id: | IJRTI2603032 |
| Published In: | Volume 11 Issue 3, March-2026 |
| DOI: | |
| Abstract: | Medication non-adherence is a major healthcare concern that can lead to treatment failure, disease progression, and increased hospitalization rates. Missed or delayed doses commonly occur due to forgetfulness, irregular daily routines, and lack of proper monitoring. This paper proposes an AI-based medicine reminder system with missed-dose prediction to improve medication adherence and patient safety. The proposed system generates scheduled reminders based on the prescribed dosage plan and continuously tracks the user’s medication intake behavior. Using machine learning techniques, the model analyzes historical adherence patterns such as timing variations, repeated delays, and frequent missed doses to predict the probability of a missed dose in advance. When a high-risk situation is detected, the system triggers proactive alerts and follow-up notifications to prevent non-adherence. Additionally, the system maintains an adherence log and provides summary reports that can support Medication non-adherence is a major healthcare concern that can lead to treatment failure, disease progression, and increased hospitalization rates. Missed or delayed doses commonly occur due to forgetfulness, irregular daily routines, and lack of proper monitoring. This paper proposes an AI-based medicine reminder system with missed-dose prediction to improve medication adherence and patient safety. The proposed system generates scheduled reminders based on the prescribed dosage plan and continuously tracks the user’s medication intake behavior. Using machine learning techniques, the model analyzes historical adherence patterns such as timing variations, repeated delays, and frequent missed doses to predict the probability of a missed dose in advance. When a high-risk situation is detected, the system triggers proactive alerts and follow-up notifications to prevent non-adherence. Additionally, the system maintains an adherence log and provides summary reports that can support |
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| Cite Article: | "A Study on Applications of Artificial Intelligence in Healthcare ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.a237-a241, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603032.pdf |
| Downloads: | 000142 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2603032
Registration ID:210050
Published In: Volume 11 Issue 3, March-2026
DOI (Digital Object Identifier):
Page No: a237-a241 Country: The Nilgiris, Tamilnadu, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2603032 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2603032 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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