Abstract
The U.S. Food and Drug Administration has authorized many narcotic (i.e., opioid) painkillers for the treatment of mild to moderately severe acute or chronic pain in humans. In recent years, there has been a sharp increase in the number of individuals who fake symptoms in order to get prescriptions for these opiates for recreational use. The purpose of this study is to develop a multi-branched system that would aid physicians in identifying and eliminating such deceptive patients. The first branch attempts to determine whether patients are faking their symptoms, while the second branch utilizes the EHR to predict how much of the prescription opioid the patient requires. This will eventually prevent patients from becoming dependent on these medications and preserve these pharmaceuticals for their intended use.
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Deolekar, R.V., Wankhade, S., Wanve, M. (2023). Decision Support System for Weeding Out Drug Seeking Behavior from Emergency Clinics. In: Smys, S., Kamel, K.A., Palanisamy, R. (eds) Inventive Computation and Information Technologies. Lecture Notes in Networks and Systems, vol 563. Springer, Singapore. https://doi.org/10.1007/978-981-19-7402-1_17
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DOI: https://doi.org/10.1007/978-981-19-7402-1_17
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