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Exploration Of Data Science Toolbox And Predictive Models To Detect And Prevent Medicare Fraud, Waste, And Abuse, Benjamin P. Goodwin, Adam Canton, Babatunde Olanipekun Mar 2023

Exploration Of Data Science Toolbox And Predictive Models To Detect And Prevent Medicare Fraud, Waste, And Abuse, Benjamin P. Goodwin, Adam Canton, Babatunde Olanipekun

SMU Data Science Review

The Federal Department of Health and Human Services spends approximately $830 Billion annually on Medicare of which an estimated $30 to $110 billion is some form of fraud, waste, or abuse (FWA). Despite the Federal Government’s ongoing auditing efforts, fraud, waste, and abuse is rampant and requires modern machine learning approaches to generalize and detect such patterns. New and novel machine learning algorithms offer hope to help detect fraud, waste, and abuse. The existence of publicly accessible datasets complied by The Centers for Medicare & Medicaid Services (CMS) contain vast quantities of structured data. This data, coupled with industry standardized …


Illicit Ketamine Induced Frequency Of Micturition In A Young Malay Woman, Noorzurani Robson Associate Prof. Dr., B. Vicknasingam, S. Narayanan May 2010

Illicit Ketamine Induced Frequency Of Micturition In A Young Malay Woman, Noorzurani Robson Associate Prof. Dr., B. Vicknasingam, S. Narayanan

Associate Prof. Dr. Noorzurani Robson

Issues. The growing use of illicit ketamine among young adults poses a public health concern in Malaysia. In contrast to medical use of ketamine, illicit use has been reported to produce adverse effects on the urinary tract and, in particular the bladder. Approach and Key Findings. This case report describes a young Malay woman who developed severe bladder symptoms (urinary frequency) after consuming illicit ketamine. A history of illicit ketamine use was initially missed, and she was consequently diagnosed and treated for a urinary tract infection. Her symptoms persisted despite several courses of antibiotics. The patient was subsequently referred to …