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Open Access
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Pradnya Patil, Sahil Sheikh, Sayali Thombare, Nikita Saindane
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- Student, Student, Student, Assistant Professor Department of Computer Engineering, Pillai HOC College of Engineering & Technology (Mumbai University) Rasayani, Department of Computer Engineering, Pillai HOC College of Engineering & Technology (Mumbai University) Rasayani, Department of Computer Engineering, Pillai HOC College of Engineering & Technology (Mumbai University) Rasayani, Department of Computer Engineering, Pillai HOC College of Engineering & Technology (Mumbai University) Rasayani Maharashtra, Maharashtra, Maharashtra, Maharashtra India, India, India, India
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Abstract
nThis paper presents the development of a novel medical report analyzer, specifically designed to streamline the interpretation of complex health data. The Report Pulse project represents a significant advancement in healthcare innovation, aiming to facilitate deeper insights into medical reports and foster personalized health management strategies. At its core, the Report Pulse project introduces a sophisticated blood report analyzer, which transcends conventional data analysis by providing actionable insights tailored to individual health needs. By harnessing cutting-edge technology, Report Pulse goes beyond merely presenting raw data, offering users personalized diet plans and essential health information derived from comprehensive report analysis. The complexity of medical reports often poses a significant challenge for individuals seeking to understand their health status. Report Pulse addresses this challenge by serving as a beacon of clarity in the realm of health data interpretation. Through intuitive design and advanced algorithms, Report Pulse demystifies the intricacies of blood reports, empowering users with invaluable insights into their health metrics. Moreover, the transformative potential of Report Pulse extends beyond individual health management. By facilitating deeper understanding of health data, Report Pulse contributes to broader healthcare innovation efforts, paving the way for more informed decision-making and enhanced patient outcomes. In summary, the Report Pulse project represents a paradigm shift in healthcare technology, offering a comprehensive solution to the complexities of medical report analysis. By combining advanced analytics with personalized insights, Report Pulse empowers users to take proactive steps towards optimizing their health and well-being.
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Keywords: Innovation, transformative, sophisticated, personalized, complexity
n[if 424 equals=”Regular Issue”][This article belongs to Journal of Computer Technology & Applications(jocta)]
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References
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- Kumar A, Goyal A, Rai BK, Sharma S. OCR based medical prescription and report analyzer. InAIP Conference Proceedings 2022 Mar 21 (Vol. 2424, No. 1). AIP Publishing.
- Shamout F, Zhu T, Clifton DA. Machine learning for clinical outcome prediction. IEEE reviews in Biomedical Engineering. 2020 Jul 7;14:116-26.
- Sumathi MS, Joshi CS, Thomas RR, Reethu G. Analysis and Performance of Machine Learning Algorithms on Disease Diagnosis. In2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies 2021 Mar 5 (pp. 1-6). IEEE.
- Nayak NK, Pooja G, Kumar RR, Spandana M, Shobha P. Health assistant bot. InEmerging Research in Computing, Information, Communication and Applications: ERCICA 2020, Volume 1 2021 Nov 16 (pp. 219-227). Singapore: Springer Singapore.
- Jhonny Pincay, Luis Terán, Edy Portmann, “Health Recommender Systems”, 2019 Sixth International Conference on eDemocracy & eGovernment (ICEDEG), Issues: April 2019.
- Dahiwade D, Patle G, Meshram E. Designing disease prediction model using machine learning approach. In2019 3rd International Conference on Computing Methodologies and Communication (ICCMC) 2019 Mar 27 (pp. 1211-1215). IEEE.
- Sharma RK, Nair AR. Efficient breast cancer prediction using ensemble machine learning models. In2019 4th International conference on recent trends on electronics, information, communication & technology (RTEICT) 2019 May 17 (pp. 100-104). IEEE.
- Teixeira F, Montenegro JL, Da Costa CA, da Rosa Righi R. An analysis of machine learning classifiers in breast cancer diagnosis. In2019 XLV Latin American computing conference (CLEI) 2019 Sep 30 (pp. 1-10). IEEE.
- Abbas H, Alic L, Rios M, Abdul-Ghani M, Qaraqe K. Predicting diabetes in healthy population through machine learning. In2019 IEEE 32nd international symposium on computer-based medical systems (CBMS) 2019 Jun 5 (pp. 567-570). IEEE.
- Krishnan S, Geetha S. Prediction of heart disease using machine learning algorithms. In2019 1st international conference on innovations in information and communication technology (ICIICT) 2019 Apr 25 (pp. 1-5). IEEE.
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| Volume | 15 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | April 6, 2024 | |
| Accepted | April 17, 2024 | |
| Published | June 29, 2024 |
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