FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308179942> ?p ?o ?g. }

• W4308179942 endingPage "e39443" @default.
• W4308179942 startingPage "e39443" @default.
• W4308179942 abstract "In knowledge transfer for educational purposes, most cancer hospital or center websites have existing information on cancer health. However, such information is usually a list of topics that are neither interactive nor customized to offer any personal touches to people facing dire health crisis and to attempt to understand the concerns of the users. Patients with cancer, their families, and the general public accessing the information are often in challenging, stressful situations, wanting to access accurate information as efficiently as possible. In addition, there is seldom any comprehensive information specifically on radiotherapy, despite the large number of older patients with cancer, to go through the treatment process. Therefore, having someone with professional knowledge who can listen to them and provide the medical information with good will and encouragement would help patients and families struggling with critical illness, particularly during the lingering pandemic.This study created a novel virtual assistant, a chatbot that can explain the radiation treatment process to stakeholders comprehensively and accurately, in the absence of any similar software. This chatbot was created using the IBM Watson Assistant with artificial intelligence and machine learning features. The chatbot or bot was incorporated into a resource that can be easily accessed by the general public.The radiation treatment process in a cancer hospital or center was described by the radiotherapy process: patient diagnosis, consultation, and prescription; patient positioning, immobilization, and simulation; 3D-imaging for treatment planning; target and organ contouring; radiation treatment planning; patient setup and plan verification; and treatment delivery. The bot was created using IBM Watson (IBM Corp) assistant. The natural language processing feature in the Watson platform allowed the bot to flow through a given conversation structure and recognize how the user responds based on recognition of similar given examples, referred to as intents during development. Therefore, the bot can be trained using the responses received, by recognizing similar responses from the user and analyzing using Watson natural language processing.The bot is hosted on a website by the Watson application programming interface. It is capable of guiding the user through the conversation structure and can respond to simple questions and provide resources for requests for information that was not directly programmed into the bot. The bot was tested by potential users, and the overall averages of the identified metrics are excellent. The bot can also acquire users' feedback for further improvements in the routine update.An artificial intelligence-assisted chatbot was created for knowledge transfer regarding radiation treatment process to the patients with cancer, their families, and the general public. The bot that is supported by machine learning was tested, and it was found that the bot can provide information about radiotherapy effectively." @default.
• W4308179942 created "2022-11-08" @default.
• W4308179942 creator A5019818750 @default.
• W4308179942 creator A5055270838 @default.
• W4308179942 creator A5082345605 @default.
• W4308179942 creator A5087585802 @default.
• W4308179942 date "2022-12-02" @default.
• W4308179942 modified "2023-09-30" @default.
• W4308179942 title "Learning the Treatment Process in Radiotherapy Using an Artificial Intelligence–Assisted Chatbot: Development Study" @default.
• W4308179942 cites W2001771035 @default.
• W4308179942 cites W2053771033 @default.
• W4308179942 cites W2054550911 @default.
• W4308179942 cites W2062205582 @default.
• W4308179942 cites W2135176533 @default.
• W4308179942 cites W22701908 @default.
• W4308179942 cites W2468014313 @default.
• W4308179942 cites W2499442869 @default.
• W4308179942 cites W2510841595 @default.
• W4308179942 cites W2753507135 @default.
• W4308179942 cites W2803131950 @default.
• W4308179942 cites W2913713488 @default.
• W4308179942 cites W2953532875 @default.
• W4308179942 cites W3011067535 @default.
• W4308179942 cites W3021673644 @default.
• W4308179942 cites W3028484854 @default.
• W4308179942 cites W3037430895 @default.
• W4308179942 cites W3103891289 @default.
• W4308179942 cites W3131571875 @default.
• W4308179942 cites W3133697945 @default.
• W4308179942 cites W3145028471 @default.
• W4308179942 cites W3170467102 @default.
• W4308179942 cites W3194625966 @default.
• W4308179942 cites W3200742808 @default.
• W4308179942 cites W4214915289 @default.
• W4308179942 cites W4307979480 @default.
• W4308179942 doi "https://doi.org/10.2196/39443" @default.
• W4308179942 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36327383" @default.
• W4308179942 hasPublicationYear "2022" @default.
• W4308179942 type Work @default.
• W4308179942 citedByCount "8" @default.
• W4308179942 countsByYear W43081799422023 @default.
• W4308179942 crossrefType "journal-article" @default.
• W4308179942 hasAuthorship W4308179942A5019818750 @default.
• W4308179942 hasAuthorship W4308179942A5055270838 @default.
• W4308179942 hasAuthorship W4308179942A5082345605 @default.
• W4308179942 hasAuthorship W4308179942A5087585802 @default.
• W4308179942 hasBestOaLocation W43081799421 @default.
• W4308179942 hasConcept C111919701 @default.
• W4308179942 hasConcept C136764020 @default.
• W4308179942 hasConcept C2779041454 @default.
• W4308179942 hasConcept C41008148 @default.
• W4308179942 hasConcept C71924100 @default.
• W4308179942 hasConcept C98045186 @default.
• W4308179942 hasConceptScore W4308179942C111919701 @default.
• W4308179942 hasConceptScore W4308179942C136764020 @default.
• W4308179942 hasConceptScore W4308179942C2779041454 @default.
• W4308179942 hasConceptScore W4308179942C41008148 @default.
• W4308179942 hasConceptScore W4308179942C71924100 @default.
• W4308179942 hasConceptScore W4308179942C98045186 @default.
• W4308179942 hasIssue "12" @default.
• W4308179942 hasLocation W43081799421 @default.
• W4308179942 hasLocation W43081799422 @default.
• W4308179942 hasLocation W43081799423 @default.
• W4308179942 hasOpenAccess W4308179942 @default.
• W4308179942 hasPrimaryLocation W43081799421 @default.
• W4308179942 hasRelatedWork W2748952813 @default.
• W4308179942 hasRelatedWork W2899084033 @default.
• W4308179942 hasRelatedWork W2956039059 @default.
• W4308179942 hasRelatedWork W2978601735 @default.
• W4308179942 hasRelatedWork W3033087304 @default.
• W4308179942 hasRelatedWork W3204793433 @default.
• W4308179942 hasRelatedWork W4232802996 @default.
• W4308179942 hasRelatedWork W4311554395 @default.
• W4308179942 hasRelatedWork W4386215362 @default.
• W4308179942 hasRelatedWork W2012842278 @default.
• W4308179942 hasVolume "6" @default.
• W4308179942 isParatext "false" @default.
• W4308179942 isRetracted "false" @default.
• W4308179942 workType "article" @default.