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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Survey: ML Techniques For Medicine Recommendation System |
| Authors Name: | Diksha Kamble , Sanjyot Khangar , Khushi Patre , Komal Shahu , Dipali Pethe |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_214174
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| Published Paper Id: | IJNRD2402259 |
| Published In: | Volume 9 Issue 2, February-2024 |
| DOI: | |
| Abstract: | ABSTRACT: Statistics mining is critical for reading big blocks of data, specifically in scientific databases. This paper provides a drug recommender gadget that makes use of patient evaluations to expect disease sentiment using various vectorization processes like Bow, TF-IDF, Word2Vec, and guide characteristic analysis. The system enables recommend the pinnacle drug for a given ailment by way of one of kind category algorithms. The LinearSVC classifier using TF-IDF vectorization outperforms all different models with 93% accuracy. The research also addresses the problem of recommending conventional herbal drugs based totally on private health information. The system uses an ontology-based understanding illustration method using net Ontology Language (OWL) to system and describes facts inside the ontology. The machine is tested on 3 scenarios: a couple of sicknesses with one-of-a-kind personal health facts, more than one illness with detailed private health information, and the identical ailment with one of a kind private health records. After evaluation through a scientific specialist, the system is observed to be capable of presenting personalized suggestions of traditional natural drug treatments and their contraindications efficaciously. |
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| Cite Article: | "Survey: ML Techniques For Medicine Recommendation System", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 2, page no.c538-c543, February-2024, Available :http://www.ijnrd.org/papers/IJNRD2402259.pdf |
| Downloads: | 000118768 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRD2402259 Registration ID: 214174 Published In: Volume 9 Issue 2, February-2024 DOI (Digital Object Identifier): Page No: c538-c543 Country: Nagpur, Maharashtra, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2402259 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2402259 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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