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1. Novel Computational Linguistic Measures, Dialogue System and the Development of SOPHIE: Standardized Online Patient for Healthcare Interaction Education

   Ali, Mohammad Rafayet; Sen, Taylan; Kane, Benjamin; Bose, Shagun; Carroll, Thomas M.; Epstein, Ronald; Schubert, Lenhart; Hoque, Mohammed Ehsan (July 2021, IEEE transactions on affective computing)

   null (Ed.)

   In this paper, we describe the iterative participatory design of SOPHIE, an online virtual patient for feedback-based practice of sensitive patient-physician conversations, and discuss an initial qualitative evaluation of the system by professional end users. The design of SOPHIE was motivated from a computational linguistic analysis of the transcripts of 383 patient-physician conversations from an essential office visit of late stage cancer patients with their oncologists. We developed methods for the automatic detection of two behavioral paradigms, lecturing and positive language usage patterns (sentiment trajectory of conversation), that are shown to be significantly associated with patient prognosis understanding. These automated metrics associated with effective communication were incorporated into SOPHIE, and a pilot user study identified that SOPHIE was favorably reviewed by a user group of practicing physicians. 

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2. Whole Genomes Reveal Evolutionary Relationships and Mechanisms Underlying Gene-Tree Discordance in Neodiprion Sawflies

   https://doi.org/10.1093/sysbio/syae036  

   Herrig, Danielle_K; Ridenbaugh, Ryan_D; Vertacnik, Kim_L; Everson, Kathryn_M; Sim, Sheina_B; Geib, Scott_M; Weisrock, David_W; Linnen, Catherine_R; Hahn, ed., Matthew (July 2024, Systematic Biology)

   Abstract Rapidly evolving taxa are excellent models for understanding the mechanisms that give rise to biodiversity. However, developing an accurate historical framework for comparative analysis of such lineages remains a challenge due to ubiquitous incomplete lineage sorting (ILS) and introgression. Here, we use a whole-genome alignment, multiple locus-sampling strategies, and summary-tree and single nucleotide polymorphism-based species-tree methods to infer a species tree for eastern North American Neodiprion species, a clade of pine-feeding sawflies (Order: Hymenopteran; Family: Diprionidae). We recovered a well-supported species tree that—except for three uncertain relationships—was robust to different strategies for analyzing whole-genome data. Nevertheless, underlying gene-tree discordance was high. To understand this genealogical variation, we used multiple linear regression to model site concordance factors estimated in 50-kb windows as a function of several genomic predictor variables. We found that site concordance factors tended to be higher in regions of the genome with more parsimony-informative sites, fewer singletons, less missing data, lower GC content, more genes, lower recombination rates, and lower D-statistics (less introgression). Together, these results suggest that ILS, introgression, and genotyping error all shape the genomic landscape of gene-tree discordance in Neodiprion. More generally, our findings demonstrate how combining phylogenomic analysis with knowledge of local genomic features can reveal mechanisms that produce topological heterogeneity across genomes. 

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3. Mining Latent Disease Factors from Medical Literature using Causality

   https://doi.org/10.1109/BigData55660.2022.10020994  

   Gujarathi, Pranav; VanSchaik, Jack T.; Mani Babu Karri, Venkata; Rajapuri, Anushri; Cheriyan, Biju; Thyvalikakath, Thankam P.; Chakraborty, Sunandan (December 2022, 2022 IEEE International Conference on Big Data (Big Data))

   Understanding causality is a longstanding goal across many different domains. Different articles, such as those published in medical journals, publish newly discovered knowledge, often causal. In this paper, we use this intuition to build a model that leverages causal relations to unearth factors related to Sjögren’s syndrome. Sjögren’s syndrome is an autoimmune disease affecting up to 3.1 million Americans. The uncommon nature of the disease, coupled with common symptoms of other autoimmune conditions such as rheumatoid arthritis, it is difficult for clinicians to timely diagnose the disease. This is further worsened by suboptimal communication between dentists, and physicians, including rheumatologists and ophthalmologists, because clinical manifestations of this disease require the patients to visit physicians with different specialties. A centralized information system with easy access to common and uncommon factors related to Sjögren’s syndrome may alleviate the problem. We use automatically extracted causal relationships from text related to Sjögren’s syndrome collected from the medical literature to identify a set of factors, such as “signs and symptoms” and “associated conditions”, related to this disease. We show that our approach is capable of retrieving such factors with high precision and recall values. Comparative experiments show that this approach leads to 25% improvement in retrieval F1-score compared to several state-of-the-art biomedical models, including BioBERT and Gram-CNN. 

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4. Complexity in sign languages

   https://doi.org/10.1515/lingvan-2021-0005  

   Malaia, Evie A.; Borneman, Joshua D.; Kurtoglu, Emre; Gurbuz, Sevgi Z.; Griffin, Darrin; Crawford, Chris; Gurbuz, Ali C. (October 2022, Linguistics Vanguard)

   Abstract Sign languages are human communication systems that are equivalent to spoken language in their capacity for information transfer, but which use a dynamic visual signal for communication. Thus, linguistic metrics of complexity, which are typically developed for linear, symbolic linguistic representation (such as written forms of spoken languages) do not translate easily into sign language analysis. A comparison of physical signal metrics, on the other hand, is complicated by the higher dimensionality (spatial and temporal) of the sign language signal as compared to a speech signal (solely temporal). Here, we review a variety of approaches to operationalizing sign language complexity based on linguistic and physical data, and identify the approaches that allow for high fidelity modeling of the data in the visual domain, while capturing linguistically-relevant features of the sign language signal. 

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5. Capturing Formality in Speech Across Domains and Languages

   https://doi.org/10.21437/Interspeech.2023-1852  

   Bhattacharya, Debasmita; Chi, Jie; Hirschberg, Julia; Bell, Peter (August 2023, Interspeech 2023)

   The linguistic notion of formality is one dimension of stylistic variation in human communication. A universal characteristic of language production, formality has surface-level realizations in written and spoken language. In this work, we explore ways of measuring the formality of such realizations in multilingual speech corpora across a wide range of domains. We compare measures of formality, contrasting textual and acoustic-prosodic metrics. We believe that a combination of these should correlate well with downstream applications. Our findings include: an indication that certain prosodic variables might play a stronger role than others; no correlation between prosodic and textual measures; limited evidence for anticipated inter-domain trends, but some evidence of consistency of measures between languages. We conclude that non-lexical indicators of formality in speech may be more subtle than our initial expectations, motivating further work on reliably encoding spoken formality. 

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