Online Textual Symptomatic Assessment Chatbot Based on Q&A Weighted Scoring for Female Breast Cancer Prescreening
Abstract
:1. Introduction
- Benefit to users: SAC’s Q&A assessment raises the awareness of FBC ailment and encourages self examination of the breasts during dialog in the comfort of the users’ valued privacy, which will stimulate them to communicate freely and sincerely about their FBC symptoms. In congruence to this regard, an earlier study by Lucas et al. [15] revealed that patients are more comfortable responding honestly to computer-administered health assessments than that of human physicians due to the “intimate” nature of information usually required in such conversational contexts. On the other hand, SAC has the ability to promptly schedule medical appointment for the users scored with positive FBC symptoms in-order to expedite timely FBC diagnosis and early medical treatment.
- Benefit to hospitals: SAC offers the potential benefit of controlling undue and inundating influx of patients in FBC healthcare departments, most of whom may schedule FBC medical appointments while having unrelated symptoms (i.e., FBC false negative cases). According to Bibault et al. [14], dialog systems can allow physicians to spend more time in treating patients who need the most consultation. On this account, the healthcare sector of many countries are beginning to utilize the digital services of chatbots for patients’ disease prescreening assessment and triage in-order to reduce stress on health providers [16]. Therefore, by adopting SAC, hospitals can drastically minimize wastage of time, money, and other resource costs, and more importantly, doctors and other healthcare personnel will be enabled to work more productively to achieve effective patient-centric care service delivery.
2. Related Works
3. Methodology
3.1. The Symptomatic Assessment Process
3.1.1. Question and Answer Distribution
3.1.2. Knowledge-Base Data Structure
3.1.3. Weighing and Scoring Module
3.2. Natural Language Understanding
3.3. The Logic Reasoning Module
4. Experimental Results
4.1. Discussion
4.2. Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Question Topic Categories | |||
---|---|---|---|
Index | Query | Index | Query |
QC1 * | Did you feel any breast lumps? | QC9 | Have you ever had a breast ultrasound examination? |
QC2 | Does the breast hurt? | QC10 | Have you ever had a mammogram? |
QC3 * | Is there any discharge from the nipple? | QC11 | Have you ever had a breast tumor lab test or breast tumor removal surgery? |
QC4 * | Is the appearance of the breast sunken, bulged, or wounded? | Q12 | Have you ever had an underarm examination or breast augmentation surgery? |
QC5 | Is any of the breast skin itchy? | QC13 | Have you ever had a breast MRI examination? |
QC6 * | Do you personally have a medical history of ovarian cancer, breast cancer, prostate cancer, or pancreatic cancer? | QC14 * | Have you had any other imaging tests in the past that show a problem with the breast? |
QC7 | Do you have direct blood relatives or siblings suffering from metastatic prostate cancer or pancreatic cancer? | QC15 * | Have you ever had a blood or genetic test confirming you are in high-risk group for breast cancer? |
QC8 | Do you have a family history of breast cancer or ovarian cancer? | QC16 * | Have you or any of your family members tested positive for breast cancer gene (BRCA)? |
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Chen, J.-H.; Agbodike, O.; Kuo, W.-L.; Wang, L.; Huang, C.-H.; Shen, Y.-S.; Chen, B.-H. Online Textual Symptomatic Assessment Chatbot Based on Q&A Weighted Scoring for Female Breast Cancer Prescreening. Appl. Sci. 2021, 11, 5079. https://doi.org/10.3390/app11115079
Chen J-H, Agbodike O, Kuo W-L, Wang L, Huang C-H, Shen Y-S, Chen B-H. Online Textual Symptomatic Assessment Chatbot Based on Q&A Weighted Scoring for Female Breast Cancer Prescreening. Applied Sciences. 2021; 11(11):5079. https://doi.org/10.3390/app11115079
Chicago/Turabian StyleChen, Jen-Hui, Obinna Agbodike, Wen-Ling Kuo, Lei Wang, Chiao-Hua Huang, Yu-Shian Shen, and Bing-Hong Chen. 2021. "Online Textual Symptomatic Assessment Chatbot Based on Q&A Weighted Scoring for Female Breast Cancer Prescreening" Applied Sciences 11, no. 11: 5079. https://doi.org/10.3390/app11115079