Mapping the Lexicon of Healthcare: Connecting ICD codes to Clinical narratives

Electronic health records are digital versions to manage and facilitate consultations and follow-up on treatments with the patients. It includes information like medical history, diagnosis, medications and test results of a patient. This digital system has been adopted by the majority of developed countries across the globe. Clinical services use ICD codes [International Classification Codes] to code the diseases and medical condition of an individual. ICD codes have a significant role in secondary purposes including funding, insurance claim processing and research. The main challenge with the use of ICD codes for a patient is to decode its meaning due to the complexity of technical medical terminology, lack of common language/context and no reference available on EHR system to direct translate it. To overcome this challenge, we would like to propose an AI-powered model to help the patients with decrypting the description of the ICD code mentioned on the medical record. The model would use unstructured clinical summaries and map it to the most relevant ICD codes. Model includes usage of Pytorch for deep model building, Flask for flexible web framework design, publicly available kaggle dataset for ICD-10 code library and clinical narrative generation and BERT (Bidirectional Encoder Representations from Transformers) for extracting the medical concepts and map them to the appropriate ICD codes. By leveraging BERT’s ability to understand and predict, we will be targeting to bridge the gap between patient comprehension and ICD Codes with an accuracy of ~ 60-80%. This will help patients to avoid any anxiety about misinterpretation, simple understandable explanations and continual usage of digital systems

Exploring Protein Interactions to Understand Gene Regulation by the Drosophila Ecdysone Receptor

The Ecdysone Receptor (EcR) is a nuclear receptor found in invertebrates, such as drosophila, that regulates gene expression during development and reproduction. While it is known that the ligand binding domain (LBD) of the ecdysone receptor binds some accessory proteins besides the ligand to regulate gene expression, protein-protein interactions with the ligand binding domain of the ecdysone receptor is understudied, and identifying the full counsel of these proteins can give major insights into how the system regulates gene expression. This project uses the Yeast Two-Hybrid (Y2H) assay to investigate novel physical interactions between the LBD of EcR and proteins in a drosophila cDNA library. The LBD is fused to the DNA binding domain of Gal4, while a drosophila library of cDNA is fused to the DNA activation domain of Gal4, creating bait and prey proteins respectively. When bait and prey are transformed into yeast, and if they interact, Gal4 transcription factor is successfully reconstituted which then activates reporter genes resulting in blue colonies and resistance to the antibiotic aureobasidin, enabling the identification of novel protein-protein interactions. A preliminary check for autoactivation was completed by transforming our bait into yeast and performing the assay to ensure that reporter genes are not activated by the LBD in the absence of the DNA activation domain. Y2H controls were also performed; the positive control confirmed interaction between known interacting proteins p53 and T-antigen and the negative control confirmed that known non-interacting proteins do not activate reporter genes. By completing the check for potential autoactivation and positive and negative controls of the Y2H assay, it was determined that the assay is functioning as designed, and further experimentation can be completed. The library screening will be completed to determine proteins that positively interact with the LBD of EcR and potentially aid in gene regulation

Next-Gen Donors: Designing a Virtual Reality Blood Donation App for Young Donors

Blood donation is a fundamental procedure in healthcare. Donors can donate blood to help those in need, but sometimes, the process may be timely and uneasy to understand. This results in a shortage of blood donations. In addition to this factor, most donors are over the age of 45 and the percentage of young adult donors ages 17 to 24 have fallen from 13.07% to 7.2% in 2022-2023 according to NHS Blood and Transplant. To encourage young adults to donate blood and establish a simple donation process, we created a blood donation app called,”The VR Blood Donation Company”. The goal of our app is to increase donor engagement, specifically in young adults, improve blood donor management, and facilitate the connection between donors. The app includes features such as virtual reality, scheduling appointments, and communication with clinics. By using frontend programming, HTML and CSS, we made the app visually appealing to the eye and through backend programming, JavaScript, the app is able to store user information and enhance the navigation of the app. Our objective is to make a positive impact on the healthcare industry and promote blood donations. The VR Blood Donation Company makes this objective possible by encouraging young adults through virtual reality and aesthetic designs, simplifying the donation process with straightforward navigation, and ultimately saving those in need

GRM-076 Assessing the Performance of Intelligent Agents in Visual Food Recognition Relative to Manual Data Entry

Accurate dietary assessment remains a critical yet time-consuming task in health and nutrition monitoring. This study benchmarks the macronutrient estimation capabilities of three intelligent vision agents: GPT Vision, Claude, and Gemini against manually logged food data. We unify two distinct datasets: MenuMatch, annotated by a professional nutritionist, and CGMacros, populated through user entries on MyFitnessPal. After flattening and cleaning both datasets, we first assess each model’s performance in calorie estimation. GPT Vision outperforms the others with the lowest percentage error 13.83% and is subsequently used to benchmark the macro estimations of Claude and Gemini. While Claude shows higher carbohydrate and fat estimation errors, Gemini yields the most balanced results across protein 12.55%, carbohydrates 19.57%, and fats 17.07%. These findings reveal strengths and trade-offs in current intelligent agents for visual food recognition, informing the development of more accurate, user-friendly, AI-powered nutrition tracking systems

Updating the phylogeography of four-toed salamanders with additional genetic sampling from the Appalachian mountains.

The four-toed salamander is found throughout a wide range in North America, which provides different environmental and geographic challenges that may structure patterns of phylogeographic diversification over time. A previous study used mitochondrial DNA sequence data to propose phylogenetic relationships between clades, finding especially high levels of haplotype diversity in the southern Appalachians. In this current study, we sought to better understand the phylogeographic relationships of the four-toed salamander within the Appalachians—including new samples collected since the completion of the previous study . We used polymerase chain reaction (PCR) and existing primers to amplify mitochondrial DNA from samples, conducted Sanger sequencing, and then aligned these sequence data with those from the previous study. We then used the data to build a phylogenetic tree and place our samples within the existing phylogenetic framework. We hope that our new data—along with larger-scale genomic data from the same samples—will help us gain a better understanding of the genetic diversity and distribution of this salamander, aiding conservation efforts. We also hope that it highlights the importance of the Appalachians as a biodiversity hotspot and in the biogeographic history of amphibians

GC-128 Multi-label commit message classification using p-tuning

Version control systems (VCS) play a crucial role by enabling developers to record changes, revert to previous versions, and coordinate work across distributed teams. In version control systems (e.g., GitHub), commit message serves as concise descriptions of code changes made during development. In our project, we propose to evaluate the performance of multi-label commit message classification using p-tuning (learnable prompt templates) through pre-trained models such as BERT and DistilBERT. The initial results show that p-tuning can provide similar results by designing various flexible templates that are not restricted by fixed templates

Evaluation of Compassion Fatigue and Perceived Organizational Support in Georgia Animal Rescues

Animal rescue volunteers often face emotionally demanding situations, making them vulnerable to compassion fatigue. Compassion fatigue (CF) combines elements of burnout with secondary traumatic stress and can impact an individual’s physical and mental health. We examined the relationship between animal rescue volunteers’ levels of CF and the degree to which they felt valued and supported by the organizations for which they volunteered (Perceived Organizational Support (POS)). We distributed surveys to 104 animal rescue organizations in Georgia, yielding 259 valid responses. Our sample was majority female (88.4%) and White (91.5%), primarily volunteering with dogs (65.3%) and cats (34.0%). The survey combined a Professional Quality of Life Scale (assessing compassion fatigue through subscales of compassion satisfaction, burnout, and secondary traumatic stress) and a shortened and modified POS scale. Our data violated normality assumptions, so we used Kendall’s tau correlation coefficient to analyze the data. Preliminary analysis revealed that POS was partially related to CF, correlating negatively with burnout (τb= -.230, p \u3c .001) and positively with compassion satisfaction (τb= .323, p \u3c .001). However, the analysis also found that POS did not correlate significantly with secondary traumatic stress, (τb= -.041, p = .353). This study is the first to compare levels of CF and POS in animal rescue volunteers. Organizations can use this information to better support their volunteers, leading to increased volunteer retention over time

Characterizing the Regulatory Environment of the Homeobox Transcription Factor ceh-27/Nkx2.1 in Nervous System Development

Transcription factors are regulatory proteins that can activate or repress gene expression by interacting with DNA sequences. Nkx2.1 is a homeodomain transcription factor in humans that is responsible for normal nervous system formation and function. Heterozygous mutations in this gene have been associated with attention deficit/hyperactivity disorder indicating a need for further study to better understand the transcriptional regulation of this gene and its role in neural development. Nkx2.1 is strongly conserved across phyla, allowing us to examine its regulatory environment in a simple model organism, such as the nematode Caenorhabditis elegans. The well characterized genome, invariant cell lineage, and simple nervous system, and the availability of powerful genetic tools, make C. elegans ideal for fundamental studies on the brain and its development. The C. elegans ortholog of Nkx2.1, called ceh-27, is a homeodomain transcription factor that is absolutely required for embryonic development and the formation of the AIYL/R interneurons. A key feature of homeodomain proteins is their DNA-binding site, and many have been identified as regulating their own transcription. The purpose of this project is to determine if ceh-27 is transcriptionally autoregulated in order to better understand the regulatory mechanisms controlling Nkx2.1 expression in humans. Data collected from 4-D timelapse microscopy assays indicate that ceh-27 works to repress its own transcription; animals with a homozygous ceh-27 mutation exhibit increased ceh-27 transcriptional activity compared to wild type organisms. Future work will identify ceh-27 autoregulatory elements along with downstream genes under the transcriptional control of ceh-27

Identification of a candidate akirin enhancer sequence

Akirin, a small nuclear protein with conserved function across eukaryotes, is a critical determinant in the development of functional, robust cardiac and skeletal patterning and musculature. Akirin serves as a transcription cofactor by acting as a link between transcription factors such as the gene Twist. Akirin uses chromatin remodeling complexes to ensure that Twist functions appropriately during transcription. If Akirin function is impaired, the resulting muscle patterning and structure is greatly impacted. We have identified a short sequence within the first intron of akirin that is highly conserved among closely related Drosophilid species. We are evaluating this sequence for possible promoter or enhancer activity. This evaluation is accomplished utilizing a variety of in vivo and in vitro techniques, both in live Drosophila embryos, as well as in cultured S2 cells. We have determined that a likely candidate enhancer sequence does indeed occur within this conserved element and are investigating a number of candidates that regulate this particular DNA sequence for akirin expression

Prototyping a User-Centered Verbal Harassment Reporting System for Social and Workplace Virtual Reality Experiences

As social VR platforms become more prevalent in daily life, they create opportunities for harmful behaviors. Studies show that users, particularly women and marginalized groups, frequently experience verbal abuse and other forms of harassment in virtual spaces, often with limited tools to report these incidents. Additionally, With more and more multi-user social VR platforms being adopted into the workplace, mitigating potential risks in a digital realm becomes a priority. This project aims to design and implement a user-centered reporting system prototype for multi-user VR applications and verify its feasibility. The VR reporting system will empower users to safely and effectively report verbal sexual harassment while preserving the immersive quality of the VR experience. Our design utilizes the game engine Unity to develop multiple scenes that allow for the testing of multiple harassment reporting UI options with the goal of understanding a bystander’s reaction and intervention to the incidents in the virtual space. Key features of the prototype include discreet reporting options, contextual guidance, and feedback mechanisms to keep users informed about the status of their reports. An informal user study will be conducted using the system prototype to collect initial user feedback to the reporting system design. Our work contributes to the broader conversation on ethical design in emerging technologies and provides practical recommendations for developers and policymakers to combat harassment in virtual space. Insights gained from the user feedback can be applied to the design of future workspace VR applications and promote positive multi-user experiences in immersive environments