M-HAJJ DSS: A mobile decision support system for Hajj pilgrims

Mohamed, Hasimah Hj; Arshad, Muhammad; Azmi, Muhammad Dzulhilmi

doi:10.1109/iccoins.2016.7783202

Cited by 7 publications

(5 citation statements)

References 7 publications

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“…They proposed a semantic-based question-and-answer system that utilizes ontology for knowledge representation. Additionally, M-Hajj [25] introduced the concept of the mobile decision support system, which utilizes case-based reasoning (CBR) and decision trees to offer optimized answers.…”

Section: Hajj Qandamentioning

confidence: 99%

Towards Reliable Healthcare LLM Agents: A Case Study for Pilgrims during Hajj

Alghamdi,

Mostafa

2024

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There is a pressing need for healthcare conversational agents with domain-specific expertise to ensure the provision of accurate and reliable information tailored to specific medical contexts. Moreover, there is a notable gap in research ensuring the credibility and trustworthiness of the information provided by these healthcare agents, particularly in critical scenarios such as medical emergencies. Pilgrims come from diverse cultural and linguistic backgrounds, often facing difficulties in accessing medical advice and information. Establishing an AI-powered multilingual chatbot can bridge this gap by providing readily available medical guidance and support, contributing to the well-being and safety of pilgrims. In this paper, we present a comprehensive methodology aimed at enhancing the reliability and efficacy of healthcare conversational agents, with a specific focus on addressing the needs of Hajj pilgrims. Our approach leverages domain-specific fine-tuning techniques on a large language model, alongside synthetic data augmentation strategies, to optimize performance in delivering contextually relevant healthcare information by introducing the HajjHealthQA dataset. Additionally, we employ a retrieval-augmented generation (RAG) module as a crucial component to validate uncertain generated responses, which improves model performance by 5%. Moreover, we train a secondary AI agent on a well-known health fact-checking dataset and use it to validate medical information in the generated responses. Our approach significantly elevates the chatbot’s accuracy, demonstrating its adaptability to a wide range of pilgrim queries. We evaluate the chatbot’s performance using quantitative and qualitative metrics, highlighting its proficiency in generating accurate responses and achieve competitive results compared to state-of-the-art models, in addition to mitigating the risk of misinformation and providing users with trustworthy health information.

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Section: Hajj Qandamentioning

confidence: 99%

Towards Reliable Healthcare LLM Agents: A Case Study for Pilgrims during Hajj

Alghamdi,

Mostafa

2024

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“…It could help in educating pilgrims in the Hajj preparation phase as well. M-Hajj [117] is a similar initiative that uses Case Based Reasoning (CBR) and Decision Trees to come up with the optimal answers. It was implemented on Android as a proof for the concept of the Mobile Decision Support System (M-DSS).…”

Section: Expert Systems and Learningmentioning

confidence: 99%

Solving Hajj and Umrah Challenges Using Information and Communication Technology: A Survey

Showail

2022

IEEE Access

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Hajj and Umrah are Muslims' religious pilgrimages to Makkah, Saudi Arabia. Hajj is considered the largest annual gathering in the world. In Islam, each and every able-bodied adult is obligated to go for Hajj at least once in his/her lifetime. Hajj takes place between the 8 th and the 13 th day of Dhul Hijjah, which is the last month of the Islamic year while Umrah, the minor pilgrimage, could be done any time of the year. In Hajj, pilgrims, also known as Hajjis, travel around 15 km and pilgrims have the choice to do it by foot, bus or by train. The Hajj journey starts from Mina, which is considered the largest tent city in the world because it hosts more than 10,000 fire resistant tents, and includes various religious rituals. Around 3 million Muslims from more than 183 countries make Hajj every year and the Kingdom of Saudi Arabia is working on increasing this number. Since 1989, researchers in various ICT domains have tried leveraging their expertise in solving challenges and issues related to Hajj and Umrah. Although several papers have surveyed efforts using technology in Hajj and Umrah research, none of them was comprehensive. In this paper, I classified research efforts that used information and communication technologies for solving Hajj and Umrah challenges over the past 33 years based on their applications in 10 categories. I also identified more than 30 technologies used by researchers all over the world to address Hajj and Umrah issues and group research efforts based on these technologies for ease of access. Furthermore, open challenges were discussed and new technologies that could be used to address these challenges were proposed.

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“…Similarly, reference [75] proposed a dynamic knowledge-based approach that facilitated a decision support system used by pilgrims to query information from dynamic knowledge-based records. The system also enabled pilgrims to contact experts, in order to obtain suitable possible solutions to their queries.…”

Section: Current Mobile Qa Systems For Pilgrimage Domainmentioning

confidence: 99%

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Arbaaeen

Shah

2021

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For many users of natural language processing (NLP), it can be challenging to obtain concise, accurate and precise answers to a question. Systems such as question answering (QA) enable users to ask questions and receive feedback in the form of quick answers to questions posed in natural language, rather than in the form of lists of documents delivered by search engines. This task is challenging and involves complex semantic annotation and knowledge representation. This study reviews the literature detailing ontology-based methods that semantically enhance QA for a closed domain, by presenting a literature review of the relevant studies published between 2000 and 2020. The review reports that 83 of the 124 papers considered acknowledge the QA approach, and recommend its development and evaluation using different methods. These methods are evaluated according to accuracy, precision, and recall. An ontological approach to semantically enhancing QA is found to be adopted in a limited way, as many of the studies reviewed concentrated instead on NLP and information retrieval (IR) processing. While the majority of the studies reviewed focus on open domains, this study investigates the closed domain.

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M-HAJJ DSS: A mobile decision support system for Hajj pilgrims

Cited by 7 publications

References 7 publications

Towards Reliable Healthcare LLM Agents: A Case Study for Pilgrims during Hajj

Towards Reliable Healthcare LLM Agents: A Case Study for Pilgrims during Hajj

Solving Hajj and Umrah Challenges Using Information and Communication Technology: A Survey

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

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