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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | TELEHEALTH- ONLINE HEALTHCARE |
| Authors Name: | Shubham Kaloge , Rohit Moriya , Rahul Bhujbal , Prajwal Patil |
| Unique Id: | IJSDR2303095 |
| Published In: | Volume 8 Issue 3, March-2023 |
| Abstract: | As technology is growing rapidly, most of the manual systems are being replaced and becoming automated. In this context, we are going to create an easy, faster and smooth appointment system between doctor and patient. With the development of online healthcare consultations, more and more doctors provide medical consultation services online. However, due to the poor healthcare knowledge and high consultation fees, selecting a proper doctor becomes a difficult problem for many users. We are creating a system which uses recommendation model takes the real consultation data from online as the research object, fully testifying its effectiveness. Specifically, this model would make recommendation to patients on department and doctors based on patients’ information of symptoms, diagnosis and geographical location, as well as doctor’s specialty and their department. Our system uses online video call consultation and smart recommendation system for patient with different diseases. System also recommends pathology labs for user to do different testing. online doctor recommendation model integrates ontology characteristics and disease text mining. The model gives a relatively more accurate recommendation advice. Furthermore, the model also gives full consideration on patients” location factors. As a result, the proposed online doctor recommendation model would improve patients’ online consultation experience and offline treatment convenience, enriching the value of online pre-diagnosis data. We are creating a system which uses recommendation model takes the real consultation data from online as the research object, fully testifying its effectiveness. Specifically, this model would make recommendation to patients on department and doctors based on patients’ information of symptoms, diagnosis and geographical location, as well as doctor’s specialty and their department. Our system uses online video call consultation and smart recommendation system for patient with different diseases.Telehealth: Online healthcare recommends pathology labs for user to do different testing. online doctor recommendation model integrates ontology characteristics and disease text mining. The model gives a relatively more accurate recommendation advice. Furthermore, the model also gives full consideration on patients” location factors. As a result, the proposed online doctor recommendation model would improve patients’ online consultation experience and offline treatment convenience, enriching the value of online pre-diagnosis data |
| Keywords: | Doctor consultation, Video Conference, Patient, Machine Learning, Encryption, Portal. |
| Cite Article: | "TELEHEALTH- ONLINE HEALTHCARE", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.593 - 596, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303095.pdf |
| Downloads: | 000337069 |
| Publication Details: | Published Paper ID: IJSDR2303095 Registration ID:204603 Published In: Volume 8 Issue 3, March-2023 DOI (Digital Object Identifier): Page No: 593 - 596 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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