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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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Issue: April 2026
Volume 11 | Issue 4
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Impact Factor : 8.14
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| Paper Title: | Quantum Rag AI: A Multi Path Reasoning and Cross Validation framework For Medical Intelligence |
| Authors Name: | Prof. Abhijeet More , Prof. Manjusha Jambhale , Charmiss Singh , Raunak Singh , Omkar Potdar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_210765
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| Published Paper Id: | IJRTI2603182 |
| Published In: | Volume 11 Issue 3, March-2026 |
| DOI: | https://doi.org/10.56975/ijrti.v11i3.210765 |
| Abstract: | The medical question-answering system proposed in the project provides structured answering, combining multiple interpretations, evidence retrieval, cross-validation, and confidence scoring. Although significiant growth have been done regarding improving the precision of systems similar to this one, these types of systems will remain entirely reliant upon their capability to validate every single answer they produce. As such, there will be instances where the same question could have multiple interpretations generated by the system and each interpretation will then need to have been checked against every generated answer. To ascertain that no answer will be produced without sufficient evidence for that answer, "confidence thresholds" are used. The way each question is reviewed supports the notion that if a person provides high-quality supporting evidence for an answer, then that response will be re-evaluated based upon their confidence in very strong evidence; conversely, if the supporting evidence for that response is not strong enough, then it will be considered incorrect and/or a low-confidence response will be provided to the user. The employment of a variety of farms of reasoning based on validated evidences also satisfies medical question-answering systems requirements. Outputs When the reasoning is diversified and independently verified, then the outputs are likely to be more robust and easier to interpret. The rationale behind this choice of design is to maximize what will be within the best interest of all system developers, and also create trustworthy medical quality assurance (QA) systems for their users; however, these systems will be built with user responses that are both accurate, and able to provide a uniform experience when providing support, they should also remain careful to the needs of those who use medical health care. |
| Keywords: | Medical Question Answering, Multi-Path Reasoning, Cross Validation and Evidence Based System Confidence Scoring |
| Cite Article: | "Quantum Rag AI: A Multi Path Reasoning and Cross Validation framework For Medical Intelligence", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 3, page no.b691-b700, March-2026, Available :http://www.ijrti.org/papers/IJRTI2603182.pdf |
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| 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: IJRTI2603182
Registration ID:210765
Published In: Volume 11 Issue 3, March-2026
DOI (Digital Object Identifier): https://doi.org/10.56975/ijrti.v11i3.210765
Page No: b691-b700 Country: -, -, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2603182 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2603182 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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