Fundamentals of the Integrated Use of Neural Network and Ontolinguistic Paradigms: A Comprehensive Approach

Palagin, O.; Kaverinskiy, V.; Malakhov, K.; Petrenko, M.

doi:10.1007/s10559-024-00652-z

Cited by 1 publication

(3 citation statements)

References 21 publications

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“…This continuous interaction with all relevant experts involved in the telerehabilitation process utilizes interactive intelligent methods and tools implemented within HCET. It is represented by the MedRehabBot component of the IAs subsystem for patient-centered telerehabilitation of cancer patients ( Kaverinsky & Malakhov, 2023b ; Litvin et al, 2022 ; O. Palagin, Kaverinsky, et al, 2023 ; Palagin, O.V. et al, 2024 ).…”

Section: Hybrid Cloud Environment For Telerehabilitation Medicine Hcetmentioning

confidence: 99%

“…MedRehabBot ( Kaverinsky & Malakhov, 2023a , 2023b ; Palagin, O.V. et al, 2024 ) utilizes an information model based on a composite service represented by a three-component tuple:…”

Section: Hybrid Cloud Environment For Telerehabilitation Medicine Hcetmentioning

confidence: 99%

“…This system was built using advanced computational linguistics technologies, such as OpenAI's GPT-4, ontology engineering and natural language understanding support services KEn ( K. S. Malakhov, Velychko, et al, 2023 ), and UkrVectōrēs ( K. S. Malakhov, Shchurov, et al, 2023 ). The OntoChatGPT not only enhances human-machine interaction intuitively but also serves as a strategic tool in RDWE, driving the development of innovative information systems for scientific R&D. For an in-depth overview of the OntoChatGPT RDWE system and its evolution refer to ( O. Palagin, Kaverinskiy, et al, 2023 ; Palagin, O.V. et al, 2024 ).…”

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confidence: 99%

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Innovative Hybrid Cloud Solutions For Physical Medicine and Telerehabilitation Research

Malakhov

2024

Int J Telerehab

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Purpose: The primary objective of this study was to develop and implement a Hybrid Cloud Environment for Telerehabilitation (HCET) to enhance patient care and research in the Physical Medicine and Rehabilitation (PM&R) domain. This environment aims to integrate advanced information and communication technologies to support both traditional in-person therapy and digital health solutions. Background: Telerehabilitation is emerging as a core component of modern healthcare, especially within the PM&R field. By applying digital health technologies, telerehabilitation provides continuous, comprehensive support for patient rehabilitation, bridging the gap between traditional therapy, and remote healthcare delivery. This study focuses on the design, and implementation of a hybrid HCET system tailored for the PM&R domain. Methods: The study involved the development of a comprehensive architectural and structural organization for the HCET, including a three-layer model (infrastructure, platform, service layers). Core components of the HCET were designed and implemented, such as the Hospital Information System (HIS) for PM&R, the MedRehabBot system, and the MedLocalGPT project. These components were integrated using advanced technologies like large language models (LLMs), word embeddings, and ontology-related approaches, along with APIs for enhanced functionality and interaction. Findings: The HCET system was successfully implemented and is operational, providing a robust platform for telerehabilitation. Key features include the MVP of the HIS for PM&R, supporting patient profile management, and rehabilitation goal tracking; the MedRehabBot and WhiteBookBot systems; and the MedLocalGPT project, which offers sophisticated querying capabilities, and access to extensive domain-specific knowledge. The system supports both Ukrainian and English languages, ensuring broad accessibility and usability. Interpretation: The practical implementation, and operation of the HCET system demonstrate its potential to transform telerehabilitation within the PM&R domain. By integrating advanced technologies, and providing comprehensive digital health solutions, the HCET enhances patient care, supports ongoing rehabilitation, and facilitates advanced research. Future work will focus on optimizing services and expanding language support to further improve the system's functionality and impact.

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Section: Hybrid Cloud Environment For Telerehabilitation Medicine Hcetmentioning

confidence: 99%

“…MedRehabBot ( Kaverinsky & Malakhov, 2023a , 2023b ; Palagin, O.V. et al, 2024 ) utilizes an information model based on a composite service represented by a three-component tuple:…”

Section: Hybrid Cloud Environment For Telerehabilitation Medicine Hcetmentioning

confidence: 99%

mentioning

confidence: 99%

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Innovative Hybrid Cloud Solutions For Physical Medicine and Telerehabilitation Research

Malakhov

2024

Int J Telerehab

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Fundamentals of the Integrated Use of Neural Network and Ontolinguistic Paradigms: A Comprehensive Approach

Cited by 1 publication

References 21 publications

Innovative Hybrid Cloud Solutions For Physical Medicine and Telerehabilitation Research

Innovative Hybrid Cloud Solutions For Physical Medicine and Telerehabilitation Research

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