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<p class="MsoNormal">Dear Colleagues,<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I am pleased to share our latest research that has been published Journal of Medical Internet Research (Top 5% on Scopus, CiteScore 14.4).<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">I look forward to hearing your feedback.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Title: “<b>Automatic Recommender System of Development Platforms for Smart Contract–Based Health Care Insurance Fraud Detection Solutions: Taxonomy and Performance Evaluation</b>”:<o:p></o:p></p>
<p class="MsoNormal"><a href="https://www.jmir.org/2024/1/e50730">https://www.jmir.org/2024/1/e50730</a>
<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;background:white">This study developed smart contracts to efficiently detect healthcare insurance fraud. We provided a taxonomy of fraud scenarios and implemented their detection
using a suitable blockchain platform. To automatically and efficiently select the best platform, we designed and implemented a decision map–based recommender system, supported by a taxonomy of 102 blockchain platforms.<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;background:white"><o:p> </o:p></span></p>
<div style="mso-element:para-border-div;border:none;border-bottom:solid #CCD1D5 1.0pt;padding:0in 0in 0in 0in;background:white">
<h3 style="margin-top:7.5pt;background:white;border:none;padding:0in"><span style="font-family:"Roboto",serif;color:#1A254C">Abstract<o:p></o:p></span></h3>
</div>
<p style="background:white;box-sizing: inherit;line-height:2rem;font-variant-ligatures: normal;font-variant-caps: normal;orphans: 2;text-align:start;widows: 2;-webkit-text-stroke-width: 0px;text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;word-spacing:0px">
<span class="abstract-sub-heading"><b><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">Background:</span></b></span><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">Health care insurance fraud is on the rise in
many ways, such as falsifying information and hiding third-party liability. This can result in significant losses for the medical health insurance industry. Consequently, fraud detection is crucial. Currently, companies employ auditors who manually evaluate
records and pinpoint fraud. However, an automated and effective method is needed to detect fraud with the continually increasing number of patients seeking health insurance. Blockchain is an emerging technology and is constantly evolving to meet business needs.
With its characteristics of immutability, transparency, traceability, and smart contracts, it demonstrates its potential in the health care domain. In particular, self-executable smart contracts are essential to reduce the costs associated with traditional
paradigms, which are mostly manual, while preserving privacy and building trust among health care stakeholders, including the patient and the health insurance networks. However, with the proliferation of blockchain development platform options, selecting the
right one for health care insurance can be difficult. This study addressed this void and developed an automated decision map recommender system to select the most effective blockchain platform for insurance fraud detection.<o:p></o:p></span></p>
<p style="background:white;box-sizing: inherit;line-height:2rem;font-variant-ligatures: normal;font-variant-caps: normal;orphans: 2;text-align:start;widows: 2;-webkit-text-stroke-width: 0px;text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;word-spacing:0px">
<span class="abstract-sub-heading"><b><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">Objective:</span></b></span><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">This study aims to develop smart contracts for
detecting health care insurance fraud efficiently. Therefore, we provided a taxonomy of fraud scenarios and implemented their detection using a blockchain platform that was suitable for health care insurance fraud detection. To automatically and efficiently
select the best platform, we proposed and implemented a decision map–based recommender system. For developing the decision-map, we proposed a taxonomy of 102 blockchain platforms.<o:p></o:p></span></p>
<p style="background:white;box-sizing: inherit;line-height:2rem;font-variant-ligatures: normal;font-variant-caps: normal;orphans: 2;text-align:start;widows: 2;-webkit-text-stroke-width: 0px;text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;word-spacing:0px">
<span class="abstract-sub-heading"><b><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">Methods:</span></b></span><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">We developed smart contracts for 12 fraud scenarios
that we identified in the literature. We used the top 2 blockchain platforms selected by our proposed decision-making map–based recommender system, which is tailored for health care insurance fraud. The map used our taxonomy of 102 blockchain platforms classified
according to their application domains.<o:p></o:p></span></p>
<p style="background:white;box-sizing: inherit;line-height:2rem;font-variant-ligatures: normal;font-variant-caps: normal;orphans: 2;text-align:start;widows: 2;-webkit-text-stroke-width: 0px;text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;word-spacing:0px">
<span class="abstract-sub-heading"><b><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">Results:</span></b></span><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">The recommender system demonstrated that Hyperledger
Fabric was the best blockchain platform for identifying health care insurance fraud. We validated our recommender system by comparing the performance of the top 2 platforms selected by our system. The blockchain platform taxonomy that we created revealed that
59 blockchain platforms are suitable for all application domains, 25 are suitable for financial services, and 18 are suitable for various application domains. We implemented fraud detection based on smart contracts.<o:p></o:p></span></p>
<p style="background:white;box-sizing: inherit;line-height:2rem;font-variant-ligatures: normal;font-variant-caps: normal;orphans: 2;text-align:start;widows: 2;-webkit-text-stroke-width: 0px;text-decoration-thickness: initial;text-decoration-style: initial;text-decoration-color: initial;word-spacing:0px">
<span class="abstract-sub-heading"><b><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">Conclusions:</span></b></span><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C">Our decision map recommender system, which was
based on our proposed taxonomy of 102 platforms, automatically selected the top 2 platforms, which were Hyperledger Fabric and Neo, for the implementation of health care insurance fraud detection. Our performance evaluation of the 2 platforms indicated that
Fabric surpassed Neo in all performance metrics, as depicted by our recommender system. We provided an implementation of fraud detection based on smart contracts.<o:p></o:p></span></p>
<p class="MsoNormal"><strong><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C;background:white">J Med Internet Res 2024;26:e50730</span></strong><span style="font-size:10.5pt;font-family:"Roboto",serif;color:#1A254C"><br>
<br>
<span class="article-doi"><span style="background:white"><a href="https://doi.org/10.2196/50730"><span style="color:#1E70C2">doi:10.2196/50730</span></a></span></span></span><span style="font-size:10.5pt;font-family:"Segoe UI",sans-serif;background:white"><o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Kind regards,<o:p></o:p></p>
<p class="MsoNormal">Leila<o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="color:#212121"><o:p> </o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D">---</span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D">Leila Ismail, Ph.D.</span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D">Associate Professor</span><span style="font-size:8.0pt;color:#201F1E">,
</span><span style="font-size:8.0pt;color:#1F497D">Dept. of Computer Science & Software Engineering</span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><b><i><span style="font-size:8.0pt;color:#1F497D">Founding Director of Intelligent Distributed Computing & Systems (INDUCE) Laboratory –</span></i></b><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><i><span style="font-size:8.0pt;color:#1F497D">Themed Intelligent Clouds and Smart City</span></i><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><b><i><span style="font-size:8.0pt;color:#1F497D">(Industry 5.0 AI projects and beyond)</span></i></b><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><b><i><span style="font-size:8.0pt;color:#1F497D"> </span></i></b><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><b><i><span style="font-size:8.0pt;color:#1F497D">[The sky is not the limit. Our possibilities are limitless]</span></i></b><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><i><span style="font-size:8.0pt;color:#201F1E"> </span></i><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D">College of IT, UAE University</span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D;border:none windowtext 1.0pt;padding:0in">P.O.Box 15551, Al</span><span style="font-size:8.0pt;color:#1F497D">-Ain, UAE</span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D">Telephone: +971-3-7135530<br>
Email: <a href="mailto:leila@uaeu.ac.ae">leila@uaeu.ac.ae</a> <o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D"> </span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span lang="FR" style="font-size:8.0pt;color:#1F497D">International Liaison Chair, IEEE COINS 2024</span><span lang="FR"><o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D"><a href="https://ems-urlprotect.trendmicro.com/wis/clicktime/v1/query?url=https%3a%2f%2fcoinsconf.com&umid=5d4b4933-35fc-4918-b664-ab70a1b45d52&auth=e76fb8029304125d326fbeca0cc52ed489c7dcd9-093ea5481f987614e341e8468520199ecb1b46b2"><span style="color:blue">https://coinsconf.com/</span></a></span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:black">IEEECloudCom 2024 Track Chair, Organizer and Chair of a Sepcial Session on Special Session on Next-Generation Technologies in Smart Digital Healthcare: AI, Edge, Cloud,
and Blockchain</span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:black"><a href="https://ems-urlprotect.trendmicro.com/wis/clicktime/v1/query?url=https%3a%2f%2fwww.cloudcom2024.org&umid=5d4b4933-35fc-4918-b664-ab70a1b45d52&auth=e76fb8029304125d326fbeca0cc52ed489c7dcd9-799ca6c012106348cf49771257845c34fae5aaca">https://www.cloudcom2024.org/</a>
</span><o:p></o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:8.0pt;color:#1F497D"> </span><o:p></o:p></p>
<p class="MsoNormal" style="line-height:12.0pt"><i><span style="font-size:8.0pt">ORCID:
</span></i><span style="font-size:8.0pt"><a href="https://orcid.org/0000-0003-0946-1818"><i><span style="color:blue">https://orcid.org/0000-0003-0946-1818</span></i></a></span><o:p></o:p></p>
<p class="MsoNormal" style="line-height:12.0pt"><i><span style="font-size:8.0pt">Google Scholar:
</span></i><span style="font-size:8.0pt"><a href="https://scholar.google.ae/citations?hl=en&user=TY-2fcUAAAAJ&view_op=list_works&sortby=pubdate"><i><span style="color:blue">https://scholar.google.ae/citations?hl=en&user=TY-2fcUAAAAJ&view_op=list_works&sortby=pubdate</span></i></a><i>
</i></span><o:p></o:p></p>
<p class="MsoNormal" style="line-height:12.0pt"><i><span style="font-size:10.0pt"><o:p> </o:p></span></i></p>
<p class="MsoNormal" style="line-height:12.0pt"><i><span style="font-size:10.0pt"> </span></i><span style="font-size:10.0pt"><o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><o:p> </o:p></p>
<p class="MsoNormal" style="background:white"><span style="font-size:10.0pt"><o:p> </o:p></span></p>
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