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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21604
Article Published : 8531
Total Authors : 22438
Total Reviewer : 805
Total Countries : 159
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| Paper Title: | Smart ovarian cancer detection using IoT system |
| Authors Name: | Santhiya C , Maheswari G , Raja K , Rudhresh J , Abinaya M |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200793
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| Published Paper Id: | IJRTI2503023 |
| Published In: | Volume 10 Issue 3, March-2025 |
| DOI: | |
| Abstract: | Ovarian cancer is often diagnosed at an advanced stage, leading to poor prognosis and a high mortality rate. The detection of ovarian cancer in its early stages is critical for improving survival rates. This project proposes an innovative IOT-based system designed to provide real-time monitoring and early detection of ovarian cancer, leveraging advanced sensor technology and machine learning algorithms. The system integrates various sensors to continuously monitor vital signs and biological markers associated with ovarian cancer. These sensors gather real-time data, including hormonal fluctuations, temperature changes, and other physiological indicators that may be linked to the disease. The collected data is then analyzed using machine learning algorithms, which are trained to detect patterns that indicate the presence of ovarian cancer at an early stage. By providing continuous and non-invasive monitoring, the proposed system enables the early identification of potential health risks, allowing for prompt intervention and treatment. This approach aims to significantly improve early diagnosis, enhance patient outcomes, and reduce the overall burden of ovarian cancer by enabling timely medical interventions. Through this innovative IOT-based monitoring system, ovarian cancer management can be revolutionized, offering new opportunities for proactive healthcare. |
| Keywords: | Cancer diagnosis ,Hardware and software, deep learning ,Data analysis , Bluetooth |
| Cite Article: | "Smart ovarian cancer detection using IoT system ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.a192-a195, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503023.pdf |
| Downloads: | 000475 |
| 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: IJRTI2503023
Registration ID:200793
Published In: Volume 10 Issue 3, March-2025
DOI (Digital Object Identifier):
Page No: a192-a195 Country: Salem, Tamilnadu , India Research Area: Bio Medical Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2503023 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2503023 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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