Discovering predictive temporal patterns for Acute Kidney Injury from critical care data
AMIA Annu Symp Proc. 2024 Jan 11;2023:261-269. eCollection 2023.ABSTRACTAcute Kidney Injury is a severe clinical condition with a high risk of multi-organs complications and mortality. For this reason, early recognition is crucial. Our proposal based on a 3-window framework discovers all hidden regularities, called Approximate Predictive Functional Dependencies, with the aim to enable early recognition of high-risk patients during hospitalization in the Intensive Care Unit (ICU). We evaluated the different severity stages according to the Kidney Disease Improving Global Outcomes (KDIGO) guidelines, building different patho...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Beatrice Amico Carlo Combi Giovanni Gambaro Source Type: research
Use GPT-J Prompt Generation with RoBERTa for NER Models on Diagnosis Extraction of Periodontal Diagnosis from Electronic Dental Records
This study explored the usability of prompt generation on named entity recognition (NER) tasks and the performance in different settings of the prompt. The prompt generation by GPT-J models was utilized to directly test the gold standard as well as to generate the seed and further fed to the RoBERTa model with the spaCy package. In the direct test, a lower ratio of negative examples with higher numbers of examples in prompt achieved the best results with a F1 score of 0.72. The performance revealed consistency, 0.92-0.97 in the F1 score, in all settings after training with the RoBERTa model. The study highlighted the impor...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yao-Shun Chuang Xiaoqian Jiang Chun-Teh Lee Ryan Brandon Duong Tran Oluwabunmi Tokede Muhammad F Walji Source Type: research
Promoting TEFCA with Blockchain Technology: A Decentralized Approach to Patient-centered Healthcare Data Management
This article delves into the potential of blockchain technology to promote TEFCA design. By providing an immutable and transparent ledger, blockchain ensures data integrity, openness, and patient privacy. Overall, the use of blockchain technology can help address the challenges of implementing TEFCA principles and promote patient empowerment and control over their health data, improve data interoperability, and enhance healthcare quality.PMID:38222410 | PMC:PMC10785864 (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yan Zhuang Luxia Zhang Source Type: research
Framework for Research in Equitable Synthetic Control Arms
AMIA Annu Symp Proc. 2024 Jan 11;2023:530-539. eCollection 2023.ABSTRACTRandomized Clinical Trials (RCTs) measure an intervention's efficacy, but they may not be generalizable to a desired target population if the RCT is not equitable. Thus, representativeness of RCTs has become a national priority. Synthetic Controls (SCs) that incorporate observational data into RCTs have shown great potential to produce more efficient studies, but their equity is rarely considered. Here, we examine how to improve treatment effect estimation and equity of a trial by augmenting "on-trial" concurrent controls with SCs to form a Hybrid Cont...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Naffs Neehal Vibha Anand Kristin P Bennett Source Type: research
Real-World Analysis of Antipsychotic Drugs' Effect on Weight Gain: An EHR Application
AMIA Annu Symp Proc. 2024 Jan 11;2023:961-968. eCollection 2023.NO ABSTRACTPMID:38222412 | PMC:PMC10785896 (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Shraddha Gupta Xing Song Source Type: research
An Automated Strategy to Calculate Medication Regimen Complexity
AMIA Annu Symp Proc. 2024 Jan 11;2023:1077-1086. eCollection 2023.ABSTRACTUnderstanding medication regimen complexity is important to understand what patients may benefit from pharmacist interventions. Medication Regimen Complexity Index (MRCI), a 65-item tool to quantify the complexity by incorporating the count, dosage form, frequency, and additional administration instructions of prescription medicines, provides a more nuanced way of assessing complexity. The goal of this study was to construct and validate a computational strategy to automate the calculation of MRCI. The performance of our strategy was evaluated by com...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yuzhi Lu Ariel R Green Rosalphie Quiles Casey Overby Taylor Source Type: research
A Computable Phenotype for the Identification of Sexual and Gender Minorities in Electronic Health Records
AMIA Annu Symp Proc. 2024 Jan 11;2023:1057-1066. eCollection 2023.ABSTRACTSexual gender minorities, including lesbian, gay, and bisexual (LGB) individuals face unique challenges due to discrimination, stigma, and marginalization, which negatively impact their well-being. Electronic health record (EHR) systems present an opportunity for LGB research, but accurately identifying LGB individuals in EHRs is challenging. Our study developed and validated a rule-based computable phenotype (CP) to identify LGB individuals and their subgroups using both structured data and unstructured clinical narratives from a large integrated he...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yongqiu Li Xing He Christopher Wheldon Yonghui Wu Mattia Prosperi Elizabeth A Shenkman Michael S Jaffee Jingchuan Guo Fei Wang Yi Guo Jiang Bian Source Type: research
Local Contrastive Learning for Medical Image Recognition
AMIA Annu Symp Proc. 2024 Jan 11;2023:1236-1245. eCollection 2023.ABSTRACTThe proliferation of Deep Learning (DL)-based methods for radiographic image analysis has created a great demand for expert-labeled radiology data. Recent self-supervised frameworks have alleviated the need for expert labeling by obtaining supervision from associated radiology reports. These frameworks, however, struggle to distinguish the subtle differences between different pathologies in medical images. Additionally, many of them do not provide interpretation between image regions and text, making it difficult for radiologists to assess model pred...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Syed A Rizvi Ruixiang Tang Xiaoqian Jiang Xiaotian Ma Xia Hu Source Type: research
The SMART Text2FHIR Pipeline
Conclusion: Future work should include mapping more categories of NLP-extracted information into FHIR resources and mappings from additional open-source NLP tools.PMID:38222416 | PMC:PMC10785871 (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Timothy A Miller Andrew J McMurry James Jones Daniel Gottlieb Kenneth D Mandl Source Type: research
Text Classification of Cancer Clinical Trial Eligibility Criteria
In this study, we focus on seven common exclusion criteria in cancer trials: prior malignancy, human immunodeficiency virus, hepatitis B, hepatitis C, psychiatric illness, drug/substance abuse, and autoimmune illness. Our dataset consists of 764 phase III cancer trials with these exclusions annotated at the trial level. We experiment with common transformer models as well as a new pre-trained clinical trial BERT model. Our results demonstrate the feasibility of automatically classifying common exclusion criteria. Additionally, we demonstrate the value of a pre-trained language model specifically for clinical trials, which ...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yumeng Yang Soumya Jayaraj Ethan Ludmir Kirk Roberts Source Type: research
MentalHealthAI: Utilizing Personal Health Device Data to Optimize Psychiatry Treatment
AMIA Annu Symp Proc. 2024 Jan 11;2023:641-652. eCollection 2023.ABSTRACTMental health disorders remain a significant challenge in modern healthcare, with diagnosis and treatment often relying on subjective patient descriptions and past medical history. To address this issue, we propose a personalized mental health tracking and mood prediction system that utilizes patient physiological data collected through personal health devices. Our system leverages a decentralized learning mechanism that combines transfer and federated machine learning concepts using smart contracts, allowing data to remain on users' devices and enabli...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Manan Shukla Oshani Seneviratne Source Type: research
Fatigue, Pain, and Medication: Mining Online Posts Regarding Rheumatoid Arthritis From Reddit
This study demonstrates the potential of using text-mining techniques on social media data to learn the treatment experiments of RA patients.PMID:38222419 | PMC:PMC10785940 (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Yi Xin Congning Ni Qingyuan Song Zhijun Yin Source Type: research
Analyzing Patient-Provided Responses to Improve Collection of Health Equity Data Elements
AMIA Annu Symp Proc. 2024 Jan 11;2023:569-578. eCollection 2023.ABSTRACTSelf-report is purported to be the gold standard for collecting demographic information. Many entry forms include a free-text "write-in" option in addition to structured responses. Balancing the flexibility of free-text with the value of collecting data in a structured format is a challenge if the data are to be useful for measuring and mitigating health disparities. While much work has been done to improve collection of race and ethnicity information, how to best collect data related to sexual and gender minority status and military veteran status has...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Jennifer Prey Dawson Heather Finn Aliasgar Z Chittalia David K Vawdrey Source Type: research
Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load
AMIA Annu Symp Proc. 2024 Jan 11;2023:389-396. eCollection 2023.ABSTRACTThe effectiveness of digital treatments can be measured by requiring patients to self-report their state through applications, however, it can be overwhelming and causes disengagement. We conduct a study to explore the impact of gamification on self-reporting. Our approach involves the creation of a system to assess cognitive load (CL) through the analysis of photoplethysmography (PPG) signals. The data from 11 participants is utilized to train a machine learning model to detect CL. Subsequently, we create two versions of surveys: a gamified and a trad...
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Michal K Grzeszczyk Paulina Adamczyk Sylwia Marek Ryszard Pr ęcikowski Maciej Ku ś M Patrycja Lelujko Rosmary Blanco Tomasz Trzci ński Arkadiusz Sitek Maciej Malawski Aneta Lisowska Source Type: research
Auditing Learned Associations in Deep Learning Approaches to Extract Race and Ethnicity from Clinical Text
We present an approach to audit the learned associations of models trained to identify RE information in clinical text by measuring the concordance between model-derived salient features and manually identified RE-related spans of text. We show that while models perform well on the surface, there exist concerning learned associations and potential for future harms from RE-identification models if left unaddressed.PMID:38222422 | PMC:PMC10785932 (Source: AMIA Annual Symposium Proceedings)
Source: AMIA Annual Symposium Proceedings - January 15, 2024 Category: Bioinformatics Authors: Oliver J Bear Don't Walk Iv Adrienne Pichon Harry Reyes Nieva Tony Sun Jaan Altosaar Karthik Natarajan Adler Perotte Peter Tarczy-Hornoch Dina Demner-Fushman No émie Elhadad Source Type: research
