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Title |
AIMS: AI based Mental Healthcare System |
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Author |
Ibrahim Alrashide, Hussain Alkhalifah, Abdul-Aziz Al-Momen, Ibrahim Alali, Ghazy Alshaikh, Atta-ur Rahman, Ashraf Saadeldeen, Khalid Aloup |
| Citation |
Vol. 23 No. 12 pp. 225-234 |
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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. |
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Keywords |
Mental health, AI, chatbot, NLP, prediction, Machine Learning, Information and Communication Technology (ICT) |
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