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Journal of the American Medical Informatics Association : JAMIA

https://read.qxmd.com/read/38547500/correction-to-from-illness-management-to-quality-of-life-rethinking-consumer-health-informatics-opportunities-for-progressive-potentially-fatal-illnesses
#1
(no author information available yet)
No abstract text is available yet for this article.
March 28, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38531680/multimodal-learning-for-temporal-relation-extraction-in-clinical-texts
#2
JOURNAL ARTICLE
Timotej Knez, Slavko Žitnik
OBJECTIVES: This study focuses on refining temporal relation extraction within medical documents by introducing an innovative bimodal architecture. The overarching goal is to enhance our understanding of narrative processes in the medical domain, particularly through the analysis of extensive reports and notes concerning patient experiences. MATERIALS AND METHODS: Our approach involves the development of a bimodal architecture that seamlessly integrates information from both text documents and knowledge graphs...
March 26, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38531679/perspectives-on-the-role-of-industry-in-informatics-research-and-authorship
#3
JOURNAL ARTICLE
Howard R Strasberg, Gretchen Purcell Jackson, Suzanne R Bakken, Aziz Boxwala, Joshua E Richardson, Jon D Morrow
OBJECTIVES: Advances in informatics research come from academic, nonprofit, and for-profit industry organizations, and from academic-industry partnerships. While scientific studies of commercial products may offer critical lessons for the field, manuscripts authored by industry scientists are sometimes categorically rejected. We review historical context, community perceptions, and guidelines on informatics authorship. PROCESS: We convened an expert panel at the American Medical Informatics Association 2022 Annual Symposium to explore the role of industry in informatics research and authorship with community input...
March 26, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38531676/preparing-for-the-bedside-optimizing-a-postpartum-depression-risk-prediction-model-for-clinical-implementation-in-a-health-system
#4
JOURNAL ARTICLE
Yifan Liu, Rochelle Joly, Meghan Reading Turchioe, Natalie Benda, Alison Hermann, Ashley Beecy, Jyotishman Pathak, Yiye Zhang
OBJECTIVE: We developed and externally validated a machine-learning model to predict postpartum depression (PPD) using data from electronic health records (EHRs). Effort is under way to implement the PPD prediction model within the EHR system for clinical decision support. We describe the pre-implementation evaluation process that considered model performance, fairness, and clinical appropriateness. MATERIALS AND METHODS: We used EHR data from an academic medical center (AMC) and a clinical research network database from 2014 to 2020 to evaluate the predictive performance and net benefit of the PPD risk model...
March 26, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38531675/development-and-internal-validation-of-a-dynamic-fall-risk-prediction-and-monitoring-tool-in-aged-care-using-routinely-collected-electronic-health-data-a-landmarking-approach
#5
JOURNAL ARTICLE
Nasir Wabe, Isabelle Meulenbroeks, Guogui Huang, Sandun Malpriya Silva, Leonard C Gray, Jacqueline C T Close, Stephen Lord, Johanna I Westbrook
OBJECTIVES: Falls pose a significant challenge in residential aged care facilities (RACFs). Existing falls prediction tools perform poorly and fail to capture evolving risk factors. We aimed to develop and internally validate dynamic fall risk prediction models and create point-based scoring systems for residents with and without dementia. MATERIALS AND METHODS: A longitudinal cohort study using electronic data from 27 RACFs in Sydney, Australia. The study included 5492 permanent residents, with a 70%-30% split for training and validation...
March 26, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38527272/the-potential-and-limitations-of-large-language-models-in-identification-of-the-states-of-motivations-for-facilitating-health-behavior-change
#6
JOURNAL ARTICLE
Michelle Bak, Jessie Chin
IMPORTANCE: The study highlights the potential and limitations of the Large Language Models (LLMs) in recognizing different states of motivation to provide appropriate information for behavior change. Following the Transtheoretical Model (TTM), we identified the major gap of LLMs in responding to certain states of motivation through validated scenario studies, suggesting future directions of LLMs research for health promotion. OBJECTIVES: The LLMs-based generative conversational agents (GAs) have shown success in identifying user intents semantically...
March 25, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38520725/ensemble-pretrained-language-models-to-extract-biomedical-knowledge-from-literature
#7
JOURNAL ARTICLE
Zhao Li, Qiang Wei, Liang-Chin Huang, Jianfu Li, Yan Hu, Yao-Shun Chuang, Jianping He, Avisha Das, Vipina Kuttichi Keloth, Yuntao Yang, Chiamaka S Diala, Kirk E Roberts, Cui Tao, Xiaoqian Jiang, W Jim Zheng, Hua Xu
OBJECTIVES: The rapid expansion of biomedical literature necessitates automated techniques to discern relationships between biomedical concepts from extensive free text. Such techniques facilitate the development of detailed knowledge bases and highlight research deficiencies. The LitCoin Natural Language Processing (NLP) challenge, organized by the National Center for Advancing Translational Science, aims to evaluate such potential and provides a manually annotated corpus for methodology development and benchmarking...
March 23, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38520723/unmasking-bias-in-artificial-intelligence-a-systematic-review-of-bias-detection-and-mitigation-strategies-in-electronic-health-record-based-models
#8
JOURNAL ARTICLE
Feng Chen, Liqin Wang, Julie Hong, Jiaqi Jiang, Li Zhou
OBJECTIVES: Leveraging artificial intelligence (AI) in conjunction with electronic health records (EHRs) holds transformative potential to improve healthcare. However, addressing bias in AI, which risks worsening healthcare disparities, cannot be overlooked. This study reviews methods to handle various biases in AI models developed using EHR data. MATERIALS AND METHODS: We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, analyzing articles from PubMed, Web of Science, and IEEE published between January 01, 2010 and December 17, 2023...
March 23, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38516861/correction-to-barriers-and-facilitators-to-the-implementation-of-family-cancer-history-collection-tools-in-oncology-clinical-practices
#9
(no author information available yet)
No abstract text is available yet for this article.
March 21, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38511501/leveraging-large-language-models-to-foster-equity-in-healthcare
#10
JOURNAL ARTICLE
Jorge A Rodriguez, Emily Alsentzer, David W Bates
OBJECTIVES: Large language models (LLMs) are poised to change care delivery, but their impact on health equity is unclear. While marginalized populations have been historically excluded from early technology developments, LLMs present an opportunity to change our approach to developing, evaluating, and implementing new technologies. In this perspective, we describe the role of LLMs in supporting health equity. MATERIALS AND METHODS: We apply the National Institute on Minority Health and Health Disparities (NIMHD) research framework to explore the use of LLMs for health equity...
March 20, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38497983/an-interpretable-predictive-deep-learning-platform-for-pediatric-metabolic-diseases
#11
JOURNAL ARTICLE
Hamed Javidi, Arshiya Mariam, Lina Alkhaled, Kevin M Pantalone, Daniel M Rotroff
OBJECTIVES: Metabolic disease in children is increasing worldwide and predisposes a wide array of chronic comorbid conditions with severe impacts on quality of life. Tools for early detection are needed to promptly intervene to prevent or slow the development of these long-term complications. MATERIALS AND METHODS: No clinically available tools are currently in widespread use that can predict the onset of metabolic diseases in pediatric patients. Here, we use interpretable deep learning, leveraging longitudinal clinical measurements, demographical data, and diagnosis codes from electronic health record data from a large integrated health system to predict the onset of prediabetes, type 2 diabetes (T2D), and metabolic syndrome in pediatric cohorts...
March 18, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38497958/leveraging-large-language-models-for-generating-responses-to-patient-messages-a-subjective-analysis
#12
JOURNAL ARTICLE
Siru Liu, Allison B McCoy, Aileen P Wright, Babatunde Carew, Julian Z Genkins, Sean S Huang, Josh F Peterson, Bryan Steitz, Adam Wright
OBJECTIVE: This study aimed to develop and assess the performance of fine-tuned large language models for generating responses to patient messages sent via an electronic health record patient portal. MATERIALS AND METHODS: Utilizing a dataset of messages and responses extracted from the patient portal at a large academic medical center, we developed a model (CLAIR-Short) based on a pre-trained large language model (LLaMA-65B). In addition, we used the OpenAI API to update physician responses from an open-source dataset into a format with informative paragraphs that offered patient education while emphasizing empathy and professionalism...
March 18, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38497957/generalizing-parkinson-s-disease-detection-using-keystroke-dynamics-a-self-supervised-approach
#13
JOURNAL ARTICLE
Shikha Tripathi, Alejandro Acien, Ashley A Holmes, Teresa Arroyo-Gallego, Luca Giancardo
OBJECTIVE: Passive monitoring of touchscreen interactions generates keystroke dynamic signals that can be used to detect and track neurological conditions such as Parkinson's disease (PD) and psychomotor impairment with minimal burden on the user. However, this typically requires datasets with clinically confirmed labels collected in standardized environments, which is challenging, especially for a large subject pool. This study validates the efficacy of a self-supervised learning method in reducing the reliance on labels and evaluates its generalizability...
March 18, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38497946/genomics-in-nephrology-identifying-informatics-opportunities-to-improve-diagnosis-of-genetic-kidney-disorders-using-a-human-centered-design-approach
#14
JOURNAL ARTICLE
Katrina M Romagnoli, Zachary M Salvati, Darren K Johnson, Heather M Ramey, Alexander R Chang, Marc S Williams
BACKGROUND: Genomic kidney conditions often have a long lag between onset of symptoms and diagnosis. To design a real time genetic diagnosis process that meets the needs of nephrologists, we need to understand the current state, barriers, and facilitators nephrologists and other clinicians who treat kidney conditions experience, and identify areas of opportunity for improvement and innovation. METHODS: Qualitative in-depth interviews were conducted with nephrologists and internists from 7 health systems...
March 18, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38489543/a-comparative-analysis-of-spanish-clinical-encoder-based-models-on-ner-and-classification-tasks
#15
JOURNAL ARTICLE
Guillem García Subies, Álvaro Barbero Jiménez, Paloma Martínez Fernández
OBJECTIVES: This comparative analysis aims to assess the efficacy of encoder Language Models for clinical tasks in the Spanish language. The primary goal is to identify the most effective resources within this context. IMPORTANCE: This study highlights a critical gap in NLP resources for the Spanish language, particularly in the clinical sector. Given the vast number of Spanish speakers globally and the increasing reliance on electronic health records, developing effective Spanish language models is crucial for both clinical research and healthcare delivery...
March 15, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38489540/assessing-the-impact-of-transitioning-to-11th-revision-of-the-international-classification-of-diseases-icd-11-on-comorbidity-indices
#16
JOURNAL ARTICLE
Jean Noel Nikiema, Djeneba Thiam, Azadeh Bayani, Alexandre Ayotte, Nadia Sourial, Michèle Bally
OBJECTIVES: This study aimed to support the implementation of the 11th Revision of the International Classification of Diseases (ICD-11). We used common comorbidity indices as a case study for proactively assessing the impact of transitioning to ICD-11 for mortality and morbidity statistics (ICD-11-MMS) on real-world data analyses. MATERIALS AND METHODS: Using the MIMIC IV database and a table of mappings between the clinical modification of previous versions of ICD and ICD-11-MMS, we assembled a population whose diagnosis can be represented in ICD-11-MMS...
March 15, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38481028/centralized-interactive-phenomics-resource-an-integrated-online-phenomics-knowledgebase-for-health-data-users
#17
JOURNAL ARTICLE
Jacqueline Honerlaw, Yuk-Lam Ho, Francesca Fontin, Michael Murray, Ashley Galloway, David Heise, Keith Connatser, Laura Davies, Jeffrey Gosian, Monika Maripuri, John Russo, Rahul Sangar, Vidisha Tanukonda, Edward Zielinski, Maureen Dubreuil, Andrew J Zimolzak, Vidul A Panickan, Su-Chun Cheng, Stacey B Whitbourne, David R Gagnon, Tianxi Cai, Katherine P Liao, Rachel B Ramoni, J Michael Gaziano, Sumitra Muralidhar, Kelly Cho
OBJECTIVE: Development of clinical phenotypes from electronic health records (EHRs) can be resource intensive. Several phenotype libraries have been created to facilitate reuse of definitions. However, these platforms vary in target audience and utility. We describe the development of the Centralized Interactive Phenomics Resource (CIPHER) knowledgebase, a comprehensive public-facing phenotype library, which aims to facilitate clinical and health services research. MATERIALS AND METHODS: The platform was designed to collect and catalog EHR-based computable phenotype algorithms from any healthcare system, scale metadata management, facilitate phenotype discovery, and allow for integration of tools and user workflows...
March 13, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38481027/disparities-in-seizure-outcomes-revealed-by-large-language-models
#18
JOURNAL ARTICLE
Kevin Xie, William K S Ojemann, Ryan S Gallagher, Russell T Shinohara, Alfredo Lucas, Chloé E Hill, Roy H Hamilton, Kevin B Johnson, Dan Roth, Brian Litt, Colin A Ellis
OBJECTIVE: Large-language models (LLMs) can potentially revolutionize health care delivery and research, but risk propagating existing biases or introducing new ones. In epilepsy, social determinants of health are associated with disparities in care access, but their impact on seizure outcomes among those with access remains unclear. Here we (1) evaluated our validated, epilepsy-specific LLM for intrinsic bias, and (2) used LLM-extracted seizure outcomes to determine if different demographic groups have different seizure outcomes...
March 13, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38472144/markov-modeling-for-cost-effectiveness-using-federated-health-data-network
#19
JOURNAL ARTICLE
Markus Haug, Marek Oja, Maarja Pajusalu, Kerli Mooses, Sulev Reisberg, Jaak Vilo, Antonio Fernández Giménez, Thomas Falconer, Ana Danilović, Filip Maljkovic, Dalia Dawoud, Raivo Kolde
OBJECTIVE: To introduce 2 R-packages that facilitate conducting health economics research on OMOP-based data networks, aiming to standardize and improve the reproducibility, transparency, and transferability of health economic models. MATERIALS AND METHODS: We developed the software tools and demonstrated their utility by replicating a UK-based heart failure data analysis across 5 different international databases from Estonia, Spain, Serbia, and the United States...
March 12, 2024: Journal of the American Medical Informatics Association: JAMIA
https://read.qxmd.com/read/38471120/a-span-based-model-for-extracting-overlapping-pico-entities-from-rct-publications
#20
JOURNAL ARTICLE
Gongbo Zhang, Yiliang Zhou, Yan Hu, Hua Xu, Chunhua Weng, Yifan Peng
OBJECTIVES: Extracting PICO (Populations, Interventions, Comparison, and Outcomes) entities is fundamental to evidence retrieval. We present a novel method, PICOX, to extract overlapping PICO entities. MATERIALS AND METHODS: PICOX first identifies entities by assessing whether a word marks the beginning or conclusion of an entity. Then, it uses a multi-label classifier to assign one or more PICO labels to a span candidate. PICOX was evaluated using one of the best-performing baselines, EBM-NLP, and three more datasets, ie, PICO-Corpus and RCT publications on Alzheimer's Disease or COVID-19, using entity-level precision, recall, and F1 scores...
March 12, 2024: Journal of the American Medical Informatics Association: JAMIA
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