DOI QR코드

DOI QR Code

AIMS: AI based Mental Healthcare System

  • Ibrahim Alrashide (Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University) ;
  • Hussain Alkhalifah (Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University) ;
  • Abdul-Aziz Al-Momen (Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University) ;
  • Ibrahim Alali (Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University) ;
  • Ghazy Alshaikh (Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University) ;
  • Atta-ur Rahman (Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University) ;
  • Ashraf Saadeldeen (Department of Computer Science, Faculty of Computer Science and Information Technology, Omdurman Islamic University) ;
  • Khalid Aloup (Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University)
  • Received : 2023.12.05
  • Published : 2023.12.30

Abstract

In this era of information and communication technology (ICT), tremendous improvements have been witnessed in our daily lives. The impact of these technologies is subjective and negative or positive. For instance, ICT has brought a lot of ease and versatility in our lifestyles, on the other hand, its excessive use brings around issues related to physical and mental health etc. In this study, we are bridging these both aspects by proposing the idea of AI based mental healthcare (AIMS). In this regard, we aim to provide a platform where the patient can register to the system and take consultancy by providing their assessment by means of a chatbot. The chatbot will send the gathered information to the machine learning block. The machine learning model is already trained and predicts whether the patient needs a treatment by classifying him/her based on the assessment. This information is provided to the mental health practitioner (doctor, psychologist, psychiatrist, or therapist) as clinical decision support. Eventually, the practitioner will provide his/her suggestions to the patient via the proposed system. Additionally, the proposed system prioritizes care, support, privacy, and patient autonomy, all while using a friendly chatbot interface. By using technology like natural language processing and machine learning, the system can predict a patient's condition and recommend the right professional for further help, including in-person appointments if necessary. This not only raises awareness about mental health but also makes it easier for patients to start therapy.

Keywords

References

  1. PricewaterhouseCoopers. (n.d.). PWC Middle East Report: Why GCC governments should invest more in Mental Health. PwC. https://www.pwc.com/m1/en/mediacentre/2022/pwc-middle-east-report-why-gccgovernments-should-invest-in-mentalhealth.html#:~:text=An%20estimated%2075%25%20of%20people,disorders%20do%20not%20seek%20treatment 
  2. Altwaijri, Y., Kazdin, A. E., Al-Subaie, A., Al-Habeeb, A., Hyder, S., Bilal, L., Naseem, M. T., & De Vol, E. (2023). Lifetime prevalence and treatment of mental disorders in Saudi youth and adolescents. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-33005-5 
  3. Saudi National Health & Stress Survey. (n.d.). Saudi National Health & Stress Survey. SNHSS 0ct 2019. http://www.healthandstress.org.sa/ 
  4. Al-Subaie, A. S., Al-Habeeb, A., & Altwaijri, Y. A. (2020). Overview of the Saudi national mental health survey. International Journal of Methods in Psychiatric Research, 29(3). https://doi.org/10.1002/mpr.1835 
  5. Makki, N., Aljohani, L., Aljohani, A., Ali, S., Aljuhani, A., Alotaibi, H., Alahmadi, R., & Alharbi, A. (2022). The impact of covid-19 pandemic on mental health among high school students in Medina, Saudi Arabia. Journal of Healthcare Sciences, 02(11), 333-339. https://doi.org/10.52533/johs.2022.21101 
  6. Alqarni, A.; Rahman, A. Arabic Tweets-Based Sentiment Analysis to Investigate the Impact of COVID-19 in KSA: A Deep Learning Approach. Big Data Cogn. Comput. 2023, 7, 16. 
  7. Atta-ur-Rahman, Dash, S., Luhach, A.K. et al. A Neuro-fuzzy approach for user behaviour classification and prediction. J Cloud Comp 8, 17 (2019). https://doi.org/10.1186/s13677-019-0144-9. 
  8. Rahman, A. GRBF-NN based ambient aware realtime adaptive communication in DVB-S2. J Ambient Intell Human Comput 14, 5929-5939
  9. Rahman, Au., Dash, S. & Luhach, A.K. Dynamic MODCOD and power allocation in DVB-S2: a hybrid intelligent approach. Telecommun Syst 76, 49-61 (2021). https://doi.org/10.1007/s11235-020-00700-x. 
  10. A Rahman, IM Qureshi, AN Malik, MT Naseem, "QoS and rate enhancement in DVB-S2 using fuzzy rule-based system," Journal of Intelligent & Fuzzy Systems 30 (2), 801-810, 2016.  https://doi.org/10.3233/IFS-151802
  11. Atta-ur-Rahman, I.M. Qureshi, A.N. Malik and M.T. Naseem, "Dynamic resource allocation for OFDM systems using differential evolution and fuzzy rule base system," Journal of Intelligent & Fuzzy Systems, 26 (4), 2035-2046, 2014.  https://doi.org/10.3233/IFS-130880
  12. A Rahman, I Qureshi, A Malik, M Naseem, "A Real Time Adaptive Resource Allocation Scheme for OFDM Systems Using GRBF-Neural Networks and Fuzzy Rule Base System," International Arab Journal of Information Technology (IAJIT) 11 (6), 2014. 
  13. MT Naseem, IM Qureshi, A Rahman, MZ Muzaffar, "Novel technique for capacity maximizing in digital watermarking using fuzzy rule base," Journal of Intelligent & Fuzzy Systems 27 (5), 2497-2509, 2014.  https://doi.org/10.3233/IFS-141223
  14. A. Rahman, S.A. Alrashed and A. Abraham, "User Behaviour Classification and Prediction Using Fuzzy Rule Based System and Linear Regression," J Info Assurance and Security 12 (3), 86-93, 2017. 
  15. Atta-ur-Rahman, D. -e. -N. Zaidi, M. H. Salam and S. Jamil, "User behaviour classification using Fuzzy Rule Based System," 13th International Conference on Hybrid Intelligent Systems (HIS 2013), Gammarth, Tunisia, 2013, pp. 117-122. 
  16. Musleh, D.A.; Alkhwaja, I.; Alkhwaja, A.; Alghamdi, M.; Abahussain, H.; Alfawaz, F.; Min-Allah, N.; Abdulqader, M.M. Arabic Sentiment Analysis of YouTube Comments: NLP-Based Machine Learning Approaches for Content Evaluation. Big Data Cogn. Comput. 2023, 7, 127. 
  17. DA Musleh, TA Alkhales, RA Almakki, SE Alnajim, et al., "Twitter Arabic Sentiment Analysis to Detect Depression Using Machine Learning," Computers, Materials & Continua 71 (2), 2022. 
  18. Ahmed, M.S.; Rahman, A.; AlGhamdi, et al. Joint Diagnosis of Pneumonia, COVID-19, and Tuberculosis from Chest X-ray Images: A Deep Learning Approach. Diagnostics 2023, 13, 2562. 
  19. A Rahman, K Sultan, I Naseer, R Majeed, D Musleh, MAS Gollapalli et al., "Supervised machine learning-based prediction of COVID-19," Computers, Materials and Continua 69 (1), 21-34, 2021.  https://doi.org/10.32604/cmc.2021.013453
  20. R Zagrouba, MA Khan, A Rahman, MA Saleem, MF Mushtaq et al., "Modelling and Simulation of COVID-19 Outbreak Prediction Using Supervised Machine Learning," Computers, Materials & Continua 66 (3), 2397-2407, 2021.  https://doi.org/10.32604/cmc.2021.014042
  21. RA Naqvi, MF Mushtaq, NA Mian, MA Khan, A Rahman et al., "Coronavirus: A "Mild" Virus Turned Deadly Infection," Computers, Materials & Continua 67 (2), 2631-2646, 2021.  https://doi.org/10.32604/cmc.2021.012167
  22. S. Almouzini, M. Khemakhem, and A. Alageel, "Detecting Arabic Depressed Users from Twitter Data," Procedia Comput. Sci., vol. 163, pp. 257-265, 2019, doi: 10.1016/j.procs.2019.12.107. 
  23. Jan, F.; Rahman, A.; Busaleh, R.; Alwarthan, H.; Aljaser, S.; Al-Towailib, S.; Alshammari, S.; Alhindi, K.R.; Almogbil, A.; Bubshait, D.A.; et al. Assessing Acetabular Index Angle in Infants: A Deep Learning-Based Novel Approach. J. Imaging 2023, 9, 242. 
  24. M. M. Qureshi, F. B. Yunus, J. Li, A. Ur-Rahman, T. Mahmood and Y. A. A. Ali, "Future Prospects and Challenges of On-Demand Mobility Management Solutions," in IEEE Access, vol. 11, pp. 114864-114879, 2023, doi: 10.1109/ACCESS.2023.3324297. 
  25. L. M. Alharbi and A. M. Qamar, "Arabic Sentiment Analysis of Eateries' Reviews: Qassim region Case study," Proc. - 2021 IEEE 4th Natl. Comput. Coll. Conf. NCCC 2021, 2021. 
  26. Musleh, D.A.; Olatunji, S.O.; Almajed, A.A.; Alghamdi, A.S.; Alamoudi, B.K.; Almousa, F.S.; Aleid, R.A.; Alamoudi, S.K.; Jan, F.; Al-Mofeez, K.A.; et al. Ensemble Learning Based Sustainable Approach to Carbonate Reservoirs Permeability Prediction. Sustainability 2023, 15, 14403. 
  27. A Alhashem, A Abdulbaset, F Almudarra et al., "Diabetes Detection and Forecasting using Machine Learning Approaches: Current State-of-the-art," IJCSNS - International Journal of Computer Science and Network Security 23(10), 199-208, 2023. 
  28. R.A. Qamar, M. Sarfraz, A. Rahman, S.A. Ghauri, "Multi-Criterion Multi-UAV Task Allocation under Dynamic Conditions," Journal of King Saud University-Computer and Information Sciences 35 (9), 101734, 2023. 
  29. S. N. Alyami and S. O. Olatunji, "Application of Support Vector Machine for Arabic Sentiment Classification Using Twitter-Based Dataset," J. Inf. Knowl. Manag., vol. 19, no. 1, pp. 1-13, 2020.  https://doi.org/10.18848/2327-7998/CGP/v19i02/1-22
  30. Ahmed, M.I.B.; Alabdulkarem, H.; Alomair, F.; Aldossary, D.; Alahmari, M.; Alhumaidan, M.; Alrassan, S.; Rahman, A.; Youldash, M.; Zaman, G. A Deep-Learning Approach to Driver Drowsiness Detection. Safety 2023, 9, 65.
  31. Al-Naim M. & Al-Mudara N. Electronic Court. King Faisal University College of Computer Sciences and Information Technology, 2012. 
  32. Islam, Md. Rabiul (2023), "Raw dataset of mental health problems in female university students in Bangladesh", Mendeley Data, V3, doi: 10.17632/v7kjs729bm.3 
  33. Islam, Md. Rabiul (2023), "Raw dataset of mental health problems in female university students in Bangladesh", Mendeley Data, V3, doi: 10.17632/v7kjs729bm.3 
  34. M Mahmud, A Rahman, M Lee, JY Choi, "Evolutionary-based image encryption using RNA codons truth table," Optics & Laser Technology 121, 105818, 2020. 
  35. S Arooj, MF Khan, T Shahzad, MA Khan, MU Nasir, M Zubair et all, "Data Fusion Architecture Empowered with Deep Learning for Breast Cancer Classification," CMC-Computers, Materials & Continua, 2023. 
  36. Ahmed, M.I.B.; Alotaibi, R.B.; Al-Qahtani, R.A.; Al-Qahtani, R.S.; Al-Hetela, S.S.; Al-Matar, K.A.; Al-Saqer, N.K.; Rahman, A.; Saraireh, L.; Youldash, M.; et al. Deep Learning Approach to Recyclable Products Classification: Towards Sustainable Waste Management. Sustainability 2023, 15, 11138. 
  37. Z Alsadeq, H Alubaidan, A Aldweesh, A Rahman, T Iqbal, "A Proposed Model for Supply Chain using Blockchain Framework," IJCSNS - International Journal of Computer Science and Network Security 23 (6), pp. 91-98, 2023. 
  38. Ibrahim, N.M.; Gabr, D.G.; Rahman, A.; Musleh, D.; AlKhulaifi, D.; AlKharraa, M. Transfer Learning Approach to Seed Taxonomy: A Wild Plant Case Study. Big Data Cogn. Comput. 2023, 7, 128. 
  39. A Albassam, F Almutairi, N Majoun, R Althukair, Z Alturaiki et al, "Integration of Blockchain and Cloud Computing in Telemedicine and Healthcare," International Journal of Computer Science and Network Security 23 (6), 17-26, 2023.  https://doi.org/10.22937/IJCSNS.2023.23.6.3
  40. Sajid, N.A.; Rahman, A.; Ahmad, M. et al. Single vs. Multi-Label: The Issues, Challenges and Insights of Contemporary Classification Schemes. Appl. Sci. 2023, 13, 6804. https://doi.org/10.3390/app13116804 
  41. Gollapalli, M.; Rahman, A.; Alkharraa, M.; Saraireh, L.; AlKhulaifi, D.; Salam, A.A.; Krishnasamy, G.; Alam Khan, M.A.; Farooqui, M.; Mahmud, M.; et al. SUNFIT: A Machine Learning-Based Sustainable University Field Training Framework for Higher Education. Sustainability 2023, 15, 8057. 
  42. Talha, M.; Sarfraz, M.; Rahman, A.; Ghauri, S.A.; Mohammad, R.M.; Krishnasamy, G.; Alkharraa, M. Voting-Based Deep Convolutional Neural Networks (VB-DCNNs) for M-QAM and M-PSK Signals Classification. Electronics 2023, 12, 1913. 
  43. T. A. Khan et al., "Secure IoMT for Disease Prediction Empowered with Transfer Learning in Healthcare 5.0, the Concept and Case Study," in IEEE Access, vol. 11, pp. 39418-39430, 2023.  https://doi.org/10.1109/ACCESS.2023.3266156
  44. Musleh, D.; Alotaibi, M.; Alhaidari, F.; Rahman, A. et al., Intrusion Detection System Using Feature Extraction with Machine Learning Algorithms in IoT. J. Sens. Actuator Netw. 2023, 12, 29. 
  45. Alghamdi, A.S.; Rahman, A. Data Mining Approach to Predict Success of Secondary School Students: A Saudi Arabian Case Study. Educ. Sci. 2023, 13, 293. 
  46. MA Qureshi, M Asif, S Anwar, U Shaukat, MA Khan, A Mosavi, "Aspect Level Songs Rating Based Upon Reviews in English," Computers, Materials & Continua 74 (2), pp. 2589-2605, 2023.  https://doi.org/10.32604/cmc.2023.032173
  47. S. Abbas, S.A. Raza, M.A. Khan, A. Rahman et al., "Automated File Labeling for Heterogeneous Files Organization Using Machine Learning," Computers, Materials & Continua 74 (2), 3263-3278, 2023.  https://doi.org/10.32604/cmc.2023.032864
  48. MS Farooq, S Abbas, A Rahman, K Sultan, MA Khan, A Mosavi, "A Fused Machine Learning Approach for Intrusion Detection System," Computers, Materials & Continua 74 (2), 2607-2623, 2023.  https://doi.org/10.32604/cmc.2023.032617
  49. Alhaidari, F., Rahman, A. & Zagrouba, R. Cloud of Things: architecture, applications and challenges. J Ambient Intell Human Comput 14, 5957-5975 (2023). https://doi.org/10.1007/s12652-020-02448-3. 
  50. M Jamal, NA Zafar, D Musleh, MA Gollapalli, S Chabani, "Modeling and Verification of Aircraft Takeoff Through Novel Quantum Nets," Computers, Materials & Continua 72 (2), pp. 3331-3348, 2022.  https://doi.org/10.32604/cmc.2022.025205
  51. A. Rahman, "Memetic computing based numerical solution to Troesch problem," Journal of Intelligent and Fuzzy Systems 36 (6), 1-10, 2019.  https://doi.org/10.3233/JIFS-17063
  52. A Albahrani, ZA AL-Ali, ZY Al-Ali et al., "Smart Attendance Management System," IJCSNS 22 (6), pp. 762-770, 2022. 
  53. A. Rahman, "Optimum information embedding in digital watermarking," Journal of Intelligent and Fuzzy Systems 37 (1), pp. 553-564, 2019. https://doi.org/10.3233/JIFS-162405