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<h1 style="text-align: center">NLM DIR Seminar Schedule</h1>
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<h4>UPCOMING SEMINARS</h4>
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<ul class="font-sans-3xs sem-list">
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<li>
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<a href="/seminar/5213/detail/">March 11, 2025 <b>Sofya Garushyants</b></a><br>Tmn – bacterial anti-phage defense system
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</li>
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<li>
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<a href="/seminar/5214/detail/">March 18, 2025 <b>MG Hirsch</b></a><br>TBD
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</li>
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<li>
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<a href="/seminar/5215/detail/">March 25, 2025 <b>Yifan Yang</b></a><br>TBD
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<li>
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<a href="/seminar/5216/detail/">April 1, 2025 <b>Roman Kogay</b></a><br>TBD
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</li>
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<li>
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<a href="/seminar/5217/detail/">April 8, 2025 <b>Jaya Srivastava</b></a><br>TBD
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<h4>RECENT SEMINARS</h4>
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<!-- change object_list to recent_sem -->
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<a href="/seminar/5212/detail/">March 4, 2025 <b>Sanasar Babajanyan</b></a><br>Evolution of antivirus defense in prokaryotes depending on the environmental virus load
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</li>
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<!-- change object_list to recent_sem -->
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<li>
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<a href="/seminar/5211/detail/">Feb. 25, 2025 <b>Zhizheng Wang</b></a><br>GeneAgent: Self-verification Language Agent for Gene Set Analysis using Domain Databases
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<!-- change object_list to recent_sem -->
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<li>
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<a href="/seminar/5210/detail/">Feb. 18, 2025 <b>Samuel Lee</b></a><br>Efficient predictions of alternative protein conformations by AlphaFold2-based sequence association
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<!-- change object_list to recent_sem -->
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<li>
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<a href="/seminar/5209/detail/">Feb. 11, 2025 <b>Po-Ting Lai</b></a><br>Enhancing Biomedical Relation Extraction with Directionality
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<!-- change object_list to recent_sem -->
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<li>
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<a href="/seminar/5208/detail/">Feb. 4, 2025 <b>Victor Tobiasson</b></a><br>On the dominance of Asgard contributions to Eukaryogenesis
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</li>
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<h2>Scheduled Seminars on Jan. 12, 2023</h2>
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<div class="tablet:grid-col-4"> Speaker</div>
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<div class="tablet:grid-col-8"><strong>Ghadh Alzamzmi</strong></div>
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<div class="tablet:grid-col-4"> Time</div>
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<div class="tablet:grid-col-8"><strong>3 p.m.</strong></div>
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<div class="tablet:grid-col-4"> Presentation Title</div>
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<div class="tablet:grid-col-8"><strong> A Comparative Study of Fairness In Medical Machine Learning </strong></div>
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<div class="tablet:grid-col-4"> Location</div>
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<div class="tablet:grid-col-8"><strong> Virtual - see link below </strong></div>
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</div>
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<p class="padding-left-2">Contact <a href="mailto:NLMDIRSeminarScheduling@mail.nih.gov">NLMDIRSeminarScheduling@mail.nih.gov</a>
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with questions about this seminar.</p>
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<div class="grid-col padding-x-2 padding-bottom-2" id="textalign">
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<h4> Abstract: </h4>
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<p><p>Although the powerful applications of machine learning (ML) are revolutionizing medicine, current algorithms are not resilient against bias. Fairness in ML can be defined as measuring the potential bias in algorithms with respect to characteristics such as race, gender, age, etc. In this paper, we perform a comparative study and systematic analysis to detect bias caused by imbalanced group representation in sample medical datasets. We investigate bias in major medical tasks for three datasets: UCI Heart Disease dataset (cardiac disease classification), Stanford Diverse Dermatology Image (DDI) dataset (skin cancer prediction), and chestX-ray dataset (CXR lung segmentation). Our results show differences in the performance of the state-of-the-arts across different groups. To mitigate this disparity, we explored three bias mitigation approaches and demonstrated that integrating these approaches into ML models can improve fairness without degrading the overall performance.</p></p>
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<h4>ARCHIVES</h4>
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<ul class="font-sans-3xs sem-list">
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<li><a href="/archive_seminars/2024/"><b>2024</b> Seminars</a></li>
|
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<li><a href="/archive_seminars/2023/"><b>2023</b> Seminars</a></li>
|
||
<li><a href="/archive_seminars/2022/"><b>2022</b> Seminars</a></li>
|
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<li><a href="/archive_seminars/2021/"><b>2021</b> Seminars</a></li>
|
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<li><a href="/archive_seminars/2020/"><b>2020</b> Seminars</a></li>
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<li><a href="/archive_seminars/2019/"><b>2019</b> Seminars</a></li>
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<li><a href="/archive_seminars/2018/"><b>2018</b> Seminars</a></li>
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<li><a href="/archive_seminars/2017/"><b>2017</b> Seminars</a></li>
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<li><a href="/archive_seminars/2016/"><b>2016</b> Seminars</a></li>
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<li><a href="/archive_seminars/2015/"><b>2015</b> Seminars</a></li>
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<li><a href="/archive_seminars/2014/"><b>2014</b> Seminars</a></li>
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<li><a href="/archive_seminars/2013/"><b>2013</b> Seminars</a></li>
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<li><a href="/archive_seminars/2012/"><b>2012</b> Seminars</a></li>
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<li><a href="/archive_seminars/2011/"><b>2011</b> Seminars</a></li>
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<li><a href="/archive_seminars/2010/"><b>2010</b> Seminars</a></li>
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<li><a href="/archive_seminars/2009/"><b>2009</b> Seminars</a></li>
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