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              <text>Realization of Humanoid Doctor and Real-Time Diagnostics of Disease Using Internet of Things, Edge Impulse Platform, and ChatGPT</text>
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              <text>ChatGPT; Disease detection; Edge computing; Humanoid; Internet of Things</text>
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              <text>Humanoid doctor is an AI-based robot that featured remote bi-directional communication and is embedded with disruptive technologies. Accurate and real-time responses are the main characteristics of a humanoid doctor which diagnoses disease in a patient. The patient details are obtained by Internet of Things devices, edge devices, and text formats. The inputs from the patient are processed by the humanoid doctor, and it provides its opinion to the patient. The historical patient data are trained using cloud artificial intelligence platform and the model is tested against the patient sample data acquired using medical IoT and edge devices. Disease is identified at three different stages and analyzed. The humanoid doctor is expected to identify the diseases well in comparison with human healthcare professionals. The humanoid doctor is under-trusted because of the lack of a multi-featured accurate model, accessibility, availability, and standardization. In this letter, patient input, artificial intelligence, and response zones are encapsulated and the humanoid doctor is realized.  The Author(s) under exclusive licence to Biomedical Engineering Society 2023.</text>
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              <text>Venkataswamy R.; Janamala V.; Cherukuri R.C.</text>
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              <text>Annals of Biomedical Engineering, Vol-52, No. 4, pp. 738-740.</text>
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              <text>Springer</text>
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              <text>&lt;a href="https://doi.org/10.1007/s10439-023-03316-9" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s10439-023-03316-9&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164813620&amp;amp;doi=10.1007%2Fs10439-023-03316-9&amp;amp;partnerID=40&amp;amp;md5=598cdf7db1ebaeb7f675f7755ba34065" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85164813620&amp;amp;doi=10.1007%2fs10439-023-03316-9&amp;amp;partnerID=40&amp;amp;md5=598cdf7db1ebaeb7f675f7755ba34065&lt;/a&gt;</text>
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            <elementText elementTextId="191952">
              <text>Restricted Access</text>
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              <text>ISSN: 906964; PubMed ID: 37453975; CODEN: ABMEC</text>
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              <text>Venkataswamy R., Department of Electrical and Electronics Engineering, Christ (Deemed to be University), Kanminike, Karnataka,  Bangalore, 560074, India; Janamala V., Department of Electrical and Electronics Engineering, Christ (Deemed to be University), Kanminike, Karnataka,  Bangalore, 560074, India; Cherukuri R.C., Department of Computer Science and Engineering, Christ (Deemed to be University), Kanminike, Karnataka,  Bangalore, 560074, India</text>
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