Search Results - "Hubig, Nina"

Interpretable machine learning predicts cardiac resynchronization therapy responses from personalized biochemical and biomechanical features by Haque, Anamul, Stubbs, Doug, Hubig, Nina C, Spinale, Francis G, Richardson, William J

“…Cardiac Resynchronization Therapy (CRT) is a widely used, device-based therapy for patients with left ventricle (LV) failure. Unfortunately, many patients do…”
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DX-FloodLine: End-To-End Deep Explainable Pipeline for Real Time Flood Scene Object Detection From Multimedia Images by Humaira, Nushrat, Samadi, Vidya S., Hubig, Nina C.

“…In recent years, an alarming number of natural disasters, specifically hurricanes and floods have affected the United States. Flooding is a global crisis,…”
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Literature Analysis on Ontologies Applied in Clinical Decision Support Systems by Jing, Xia, Min, Hua, Gong, Yang, Biondich, Paul, Robinson, David, Law, Timothy D, Nohr, Christian G, Faxvaag, Arild, Rennert, Lior, Hubig, Nina C, Gimbel, Ronald W

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Ontologies Applied in Clinical Decision Support System Rules: Systematic Review by Jing, Xia, Min, Hua, Gong, Yang, Biondich, Paul, Robinson, David, Law, Timothy, Nohr, Christian, Faxvaag, Arild, Rennert, Lior, Hubig, Nina, Gimbel, Ronald

“…Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are…”
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Opening the Black Box of Family-Based Treatments: An Artificial Intelligence Framework to Examine Therapeutic Alliance and Therapist Empathy by Cunningham, Phillippe B., Gilmore, Jordon, Naar, Sylvie, Preston, Stephanie D., Eubanks, Catherine F., Hubig, Nina Christina, McClendon, Jerome, Ghosh, Samiran, Ryan-Pettes, Stacy

“…The evidence-based treatment (EBT) movement has primarily focused on core intervention content or treatment fidelity and has largely ignored practitioner…”
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PhenoMetaboDiff: R Package for Analysis and Visualization of Phenotype Microarray Data by Pauly, Rini, Iqbal, Mehtab, Lee, Narae, Moffitt, Bridgette Allen, Sarasua, Sara Moir, Li, Luyi, Hubig, Nina Christine, Boccuto, Luigi

“…Background: PhenoMetaboDiff is a novel R package for computational analysis and visualization of data generated by Biolog Phenotype Mammalian Microarrays…”
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Advancing Anomaly Detection: Non-Semantic Financial Data Encoding with LLMs by Bakumenko, Alexander, Hlaváčková-Schindler, Kateřina, Plant, Claudia, Hubig, Nina C

“…Detecting anomalies in general ledger data is of utmost importance to ensure trustworthiness of financial records. Financial audits increasingly rely on…”
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The emergence of Large Language Models (LLM) as a tool in literature reviews: an LLM automated systematic review by Scherbakov, Dmitry, Hubig, Nina, Jansari, Vinita, Bakumenko, Alexander, Lenert, Leslie A

“…Objective: This study aims to summarize the usage of Large Language Models (LLMs) in the process of creating a scientific review. We look at the range of…”
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Active Density-Based Clustering by Mai, Son T., Xiao He, Hubig, Nina, Plant, Claudia, Bohm, Christian

“…The density-based clustering algorithm DBSCAN is a fundamental technique for data clustering with many attractive properties and applications. However, DBSCAN…”
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Active Learning Pipeline to Identify Candidate Terms for a CDSS Ontology by Jing, Xia, Goli, Rohan, Komatineni, Keerthana, Alluri, Shailesh, Hubig, Nina, Min, Hua, Gong, Yang, Sittig, Dean F, Biondich, Paul, Robinson, David, Nøhr, Christian, Faxvaag, Arild, Wright, Adam, Law, Timothy, Rennert, Lior, Gimbel, Ronald

“…Ontology is essential for achieving health information and information technology application interoperability in the biomedical fields and beyond…”
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Compression-Based Graph Mining Exploiting Structure Primitives by Jing Feng, Xiao He, Hubig, Nina, Bohm, Christian, Plant, Claudia

“…How can we retrieve information from sparse graphs? Traditional graph mining approaches focus on discovering dense patterns inside complex networks, for…”
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Generalized Independent Subspace Clustering by Wei Ye, Maurus, Samuel, Hubig, Nina, Plant, Claudia

“…Data can encapsulate different object groupings in subspaces of arbitrary dimension and orientation. Finding such subspaces and the groupings within them is…”
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