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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.05856 |
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| _version_ | 1866912112903716864 |
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| author | Hossain, Soaad Rasalingam, James Waheed, Arhum Awil, Fatah Kandiah, Rachel Ahmed, Syed Ishtiaque |
| author_facet | Hossain, Soaad Rasalingam, James Waheed, Arhum Awil, Fatah Kandiah, Rachel Ahmed, Syed Ishtiaque |
| contents | With the growing interest in using AI and machine learning (ML) in medicine, there is an increasing number of literature covering the application and ethics of using AI and ML in areas of medicine such as clinical psychiatry. The problem is that there is little literature covering the economic aspects associated with using ML in clinical psychiatry. This study addresses this gap by specifically studying the economic implications of using ML in clinical psychiatry. In this paper, we evaluate the economic implications of using ML in clinical psychiatry through using three problem-oriented case studies, literature on economics, socioeconomic and medical AI, and two types of health economic evaluations. In addition, we provide details on fairness, legal, ethics and other considerations for ML in clinical psychiatry. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_05856 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Evaluating the Economic Implications of Using Machine Learning in Clinical Psychiatry Hossain, Soaad Rasalingam, James Waheed, Arhum Awil, Fatah Kandiah, Rachel Ahmed, Syed Ishtiaque Computers and Society Artificial Intelligence Computational Engineering, Finance, and Science Human-Computer Interaction Machine Learning 68T01 I.2; J.4; I.2.1; K.4.3 With the growing interest in using AI and machine learning (ML) in medicine, there is an increasing number of literature covering the application and ethics of using AI and ML in areas of medicine such as clinical psychiatry. The problem is that there is little literature covering the economic aspects associated with using ML in clinical psychiatry. This study addresses this gap by specifically studying the economic implications of using ML in clinical psychiatry. In this paper, we evaluate the economic implications of using ML in clinical psychiatry through using three problem-oriented case studies, literature on economics, socioeconomic and medical AI, and two types of health economic evaluations. In addition, we provide details on fairness, legal, ethics and other considerations for ML in clinical psychiatry. |
| title | Evaluating the Economic Implications of Using Machine Learning in Clinical Psychiatry |
| topic | Computers and Society Artificial Intelligence Computational Engineering, Finance, and Science Human-Computer Interaction Machine Learning 68T01 I.2; J.4; I.2.1; K.4.3 |
| url | https://arxiv.org/abs/2411.05856 |