Automatic Detection of Adverse Drug Events in Geriatric Care: Study Proposal

BACKGROUND One-third of older inpatients experience adverse drug events (ADEs), which increase their mortality, morbidity, and health care use and costs. In particular, antithrombotic drugs are among the most at-risk medications for this population. Reporting systems have been implemented at the national, regional, and provider levels to monitor ADEs and design prevention strategies. Owing to their well-known limitations, automated detection technologies based on electronic medical records (EMRs) are being developed to routinely detect or predict ADEs. OBJECTIVE This study aims to develop and validate an automated detection tool for monitoring antithrombotic-related ADEs using EMRs from 4 large Swiss hospitals. We aim to assess cumulative incidences of hemorrhages and thromboses in older inpatients associated with the prescription of antithrombotic drugs, identify triggering factors, and propose improvements for clinical practice. METHODS This project is a multicenter, cross-sectional study based on 2015 to 2016 EMR data from 4 large hospitals in Switzerland: Lausanne, Geneva, and Zürich university hospitals, and Baden Cantonal Hospital. We have included inpatients aged ≥65 years who stayed at 1 of the 4 hospitals during 2015 or 2016, received at least one antithrombotic drug during their stay, and signed or were not opposed to a general consent for participation in research. First, clinical experts selected a list of relevant antithrombotic drugs along with their side effects, risks, and confounding factors. Second, administrative, clinical, prescription, and laboratory data available in the form of free text and structured data were extracted from study participants' EMRs. Third, several automated rule-based and machine learning-based algorithms are being developed, allowing for the identification of hemorrhage and thromboembolic events and their triggering factors from the extracted information. Finally, we plan to validate the developed detection tools (one per ADE type) through manual medical record review. Performance metrics for assessing internal validity will comprise the area under the receiver operating characteristic curve, F$_{1}$-score, sensitivity, specificity, and positive and negative predictive values. RESULTS After accounting for the inclusion and exclusion criteria, we will include 34,522 residents aged ≥65 years. The data will be analyzed in 2022, and the research project will run until the end of 2022 to mid-2023. CONCLUSIONS This project will allow for the introduction of measures to improve safety in prescribing antithrombotic drugs, which today remain among the drugs most involved in ADEs. The findings will be implemented in clinical practice using indicators of adverse events for risk management and training for health care professionals; the tools and methodologies developed will be disseminated for new research in this field. The increased performance of natural language processing as an important complement to structured data will bring existing tools to another level of efficiency in the detection of ADEs. Currently, such systems are unavailable in Switzerland. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/40456

Utilizing mHealth to increase follow-up in Latinx adults with hyperlipidemia.

Background: Management of hyperlipidemia (HLD) is crucial to the prevention and management of cardiovascular disease cardiovascular disease (CVD), a leading cause of death in the United States (US) and Latinx adults (Centers for Disease Control and Prevention (CDC), 2019). The main difficulty affecting monitoring of lipid levels in patients diagnosed with HLD is lack of adherence to follow-up appointments. Purpose: The purpose of this Quality Improvement (QI) project is to evaluate the impact of culturally competent translated short message service (SMS) texts to increase adherence follow-up on a Latinx population served at the Kentucky Racing Services Health Center (KRSHC). Intervention: This project utilized the rapid plan, do, study, act (PDSA) cycle for quality improvement to evaluate the impact of culturally competent SMS texts appointment reminders. A retrospective review identified patients requiring intervention. Rate of change and two proportion z test was used to calculate follow-up rates and statistical significance between pre- and post-intervention groups. Results: Although not statistically significant, the rate of change was 2.7%. More than 50% of patients in both groups were male. Gender assigned at birth and age distribution were similar between both groups. Discussion: SMS text reminders are a quick and cost-effective method to communicate with Latinx patients. mHealth as a form of communication may prove to be a more effective means of communication as the population becomes more familiar with it

No One Can Whistle a Symphony: Analyzing Growth in Proficiency for English Learners in Coteaching

K-12 ELs in the U.S. are increasing in number and diversity (Park, et al., 2018), requiring schools to establish and grow language instruction education programs (LIEPs) that facilitate language acquisition for a wide range of learners, while also providing equitable opportunities to learn. The study used a quantitative, pretest-posttest, research design to address gaps in the literature noted by Takanishi & Menestrel (2017), regarding which LIEPs are most effective for various EL subgroups, and to explore the effects of Coteaching for ELs (COTEL) on growth in proficiency. Data from 723 ELs in two Midwestern districts was disaggregated three ways to determine if ELs of various home languages, grade levels, and starting proficiency levels grew more in COTEL or in other kinds of English instructed LIEPS (NO COTEL). Growth was calculated using ACCESS test scores from 2018 and 2019 to avoid pandemic effects. Several two-way analyses of covariance (ANCOVA) were conducted to control for pretest differences and to better isolate the effects of COTEL on growth in English amongst various subgroups. Results showed that overall ELs grew more in COTEL. Additionally, statistically significant, higher growth was discovered for 4th and 7th graders in COTEL, and for ELs with Developing (DEV) and Expanding (EXP) starting proficiency levels in Grades 3-5, and for all starting proficiency levels in Grades 6-8. Of particular interest, speakers of 33 lower incidence languages (MIX33) accelerated their growth in English in COTEL, while floundering in other kinds of English-instructed LIEPs (NO COTEL). Based on these findings, the researcher proposes that among English-instructed LIEPs, COTEL holds the most promise for implementing research-based practices with fidelity, for infusing a translanguaging stance, and for building the capacity of each classroom’s teachers to succeed with multilingual learners

Semantic Parsing in Limited Resource Conditions

This thesis explores challenges in semantic parsing, specifically focusing on scenarios with limited data and computational resources. It offers solutions using techniques like automatic data curation, knowledge transfer, active learning, and continual learning. For tasks with no parallel training data, the thesis proposes generating synthetic training examples from structured database schemas. When there is abundant data in a source domain but limited parallel data in a target domain, knowledge from the source is leveraged to improve parsing in the target domain. For multilingual situations with limited data in the target languages, the thesis introduces a method to adapt parsers using a limited human translation budget. Active learning is applied to select source-language samples for manual translation, maximizing parser performance in the target language. In addition, an alternative method is also proposed to utilize machine translation services, supplemented by human-translated data, to train a more effective parser. When computational resources are limited, a continual learning approach is introduced to minimize training time and computational memory. This maintains the parser's efficiency in previously learned tasks while adapting it to new tasks, mitigating the problem of catastrophic forgetting. Overall, the thesis provides a comprehensive set of methods to improve semantic parsing in resource-constrained conditions.Comment: PhD thesis, year of award 2023, 172 page

Reducing No-Shows and Late Cancellations in Primary Care

No-shows and late cancellations are a challenge across medical practices, resulting in costly, fragmented care. Many patients do not understand the impact that not showing or cancelling an appointment less than 48 hours prior to a visit can have. While reminding the patient of the appointment has been a known tactic to improve patient’s attendance, the most effective mode of the reminder can vary significantly across patient populations. Just as critical as reminding the patient of the appointment is to ensure they understand the purpose of the visit along with showing respect for their time and any competing priorities. This quality improvement initiative aimed to reduce the no-show rate of 21.4% and late cancellation rate of 21.1% for the MassHealth population by 5%. Learning from previous studies, a hybrid approach to meet this population’s needs included a 7-day reminder call with a Patient Engagement Coordinator (PEC) and a 2-day automated reminder. During the 7-day reminder call the PEC identified barriers to attending the appointment through concrete planning and motivational interviewing strategies. Appointments were rescheduled as needed, additional information was provided to solidify shared goals for the visit, and patient’s time/obligations were validated. The intervention resulted in positive feedback from the majority of patients and revealed concrete planning prompts to be a very effective communication form. The post-intervention data analysis revealed both the no-show and late cancellation results were reduced for the MassHealth population. Due to data and confounding variable limitations this study is recommended to be a basis for future investigation as the principal investigators enter into the next pilot phase of this model

Lexical Simplification System to Improve Web Accessibility

People with intellectual, language and learning disabilities face accessibility barriers when reading texts with complex words. Following accessibility guidelines, complex words can be identified, and easy synonyms and definitions can be provided for them as reading aids. To offer support to these reading aids, a lexical simplification system for Spanish has been developed and is presented in this article. The system covers the complex word identification (CWI) task and offers replacement candidates with the substitute generation and selection (SG/SS) task. These tasks have followed machine learning techniques and contextual embeddings using Easy Reading and Plain Language resources, such as dictionaries and corpora. Additionally, due to the polysemy present in the language, the system provides definitions for complex words, which are disambiguated by a rule-based method supported by a state-of-the-art embedding resource. This system is integrated into a web system that provides an easy way to improve the readability and comprehension of Spanish texts. The results obtained are satisfactory; in the CWI task, better results were obtained than with other systems that used the same dataset. The SG/SS task results are comparable to similar works in the English language and provide a solid starting point to improve this task for the Spanish language. Finally, the results of the disambiguation process evaluation were good when evaluated by a linguistic expert. These findings represent an additional advancement in the lexical simplification of texts in Spanish and in a generic domain using easy-to-read resources, among others, to provide systematic support to compliance with accessibility guidelinesThis work was supported in part by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors under Grant EPUC3M17, in part by the context of the V PRICIT (Regional Programme of Research and Technological Innovation), and in part by the Accessible Technologies Award-INDRA Technologies and the Fundación Universia (www.tecnologiasaccesibles.com

Automatic medical term generation for a low-resource language: translation of SNOMED CT into Basque

211 p. (eusk.) 148 p. (eng.)Tesi-lan honetan, terminoak automatikoki euskaratzeko sistemak garatu eta ebaluatu ditugu. Horretarako,SNOMED CT, terminologia kliniko zabala barnebiltzen duen ontologia hartu dugu abiapuntutzat, etaEuSnomed deritzon sistema garatu dugu horren euskaratzea kudeatzeko. EuSnomedek lau urratsekoalgoritmoa inplementatzen du terminoen euskarazko ordainak lortzeko: Lehenengo urratsak baliabidelexikalak erabiltzen ditu SNOMED CTren terminoei euskarazko ordainak zuzenean esleitzeko. Besteakbeste, Euskalterm banku terminologikoa, Zientzia eta Teknologiaren Hiztegi Entziklopedikoa, eta GizaAnatomiako Atlasa erabili ditugu. Bigarren urratserako, ingelesezko termino neoklasikoak euskaratzekoNeoTerm sistema garatu dugu. Sistema horrek, afixu neoklasikoen baliokidetzak eta transliterazio erregelakerabiltzen ditu euskarazko ordainak sortzeko. Hirugarrenerako, ingelesezko termino konplexuak euskaratzendituen KabiTerm sistema garatu dugu. KabiTermek termino konplexuetan agertzen diren habiaratutakoterminoen egiturak erabiltzen ditu euskarazko egiturak sortzeko, eta horrela termino konplexuakosatzeko. Azken urratsean, erregeletan oinarritzen den Matxin itzultzaile automatikoa osasun-zientziendomeinura egokitu dugu, MatxinMed sortuz. Horretarako Matxin domeinura egokitzeko prestatu dugu,eta besteak beste, hiztegia zabaldu diogu osasun-zientzietako testuak itzuli ahal izateko. Garatutako lauurratsak ebaluatuak izan dira metodo ezberdinak erabiliz. Alde batetik, aditu talde txiki batekin egin dugulehenengo bi urratsen ebaluazioa, eta bestetik, osasun-zientzietako euskal komunitateari esker egin dugunMedbaluatoia kanpainaren baitan azkeneko bi urratsetako sistemen ebaluazioa egin da

The impact of Edward Perry Warren on the study and collections of Greek and Roman antiquities in American academia.

This dissertation assesses the influence of Edward Perry Warren (1860- 1928) on the development of collegiate collections of Greek and Roman art and the rise of art history and archaeology in elite academic institutions in the United States. It employs archival research to explore Warren\u27s motivations for acquiring thousands of antiquities which he sold or gave to the Museum of Fine Arts, Boston and six collegiate museums and study collections. Organized into six chapters, this multidisciplinary dissertation describes Warren\u27s roles at these institutions. It highlights antiquities that have figured prominently in scholarship and that demonstrate the range and variety of his collecting tastes. In the first three chapters, the dissertation places Warren\u27s collecting in light of its social, economic, intellectual, and cultural backdrop and considers how Warren both reflects and diverges from his family\u27s values. It also weighs how Warren\u27s sexuality impacted his collecting tastes and resulted in the establishment of his antiquities emporium in Lewes, England. It chronicles his partnership with John Marshall, Edward Robinson, and John Davidson Beazley and ascertains what is known about his relationships with those who established the classical collections at Harvard, Bowdoin, the University of Pennsylvania, Bryn Mawr, the University of Chicago, and the Rhode Island School of Design. Chapters 4,5, and 6 function as a selective catalogue of Warren\u27s antiquities, organized by medium. Chapter 4 is devoted to a discussion of how the Greek vases and other ceramic antiquities he obtained for American collections have been pivotal in developing the American scholarship on these objects. Chapter 5 considers the impact of Warren\u27s collecting on Greek numismatics as well as on ancient gems, jewelry, ivory, and glass. Chapter 6 features bronze and stone antiquities that illustrate his connoisseurial acumen. This dissertation argues that the collecting of Edward Perry Warren is essential to understanding the rise of art history and archaeology as academic disciplines in the United States. Antiquities that he obtained for American collections continue to figure prominently in the scholarship and exhibitions focusing on Greek and Roman material culture and social history

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl