Use the keywords feature with a free QxMD account.
Use Read by QxMD to access full text via your institution or open access sources.
Read also provides personalized recommendations to keep you up to date in your field.
Existing User
Sign InNew to Read
Sign Up#21
JOURNAL ARTICLE
Gondy Leroy, Jennifer G Andrews, Madison KeAlohi-Preece, Ajay Jaswani, Hyunju Song, Maureen Kelly Galindo, Sydney A Rice
OBJECTIVE: Machine learning (ML) is increasingly employed to diagnose medical conditions, with algorithms trained to assign a single label using a black-box approach. We created an ML approach using deep learning that generates outcomes that are transparent and in line with clinical, diagnostic rules. We demonstrate our approach for autism spectrum disorders (ASD), a neurodevelopmental condition with increasing prevalence. METHODS: We use unstructured data from the Centers for Disease Control and Prevention (CDC) surveillance records labeled by a CDC-trained clinician with ASD A1-3 and B1-4 criterion labels per sentence and with ASD cases labels per record using Diagnostic and Statistical Manual of Mental Disorders (DSM5) rules...
April 16, 2024: Journal of the American Medical Informatics Association: JAMIA
#22
JOURNAL ARTICLE
Wei Nie, Bingrui Zhou, Zhiyong Wang, Bowen Chen, Xinming Wang, Chunchun Hu, Huiping Li, Qiong Xu, Xiu Xu, Honghai Liu
Interpersonal communication facilitates symptom measures of autistic sociability to enhance clinical decision-making in identifying children with autism spectrum disorder (ASD). Traditional methods are carried out by clinical practitioners with assessment scales, which are subjective to quantify. Recent studies employ engineering technologies to analyze children's behaviors with quantitative indicators, but these methods only generate specific rule-driven indicators that are not adaptable to diverse interaction scenarios...
April 16, 2024: IEEE Journal of Biomedical and Health Informatics
#23
JOURNAL ARTICLE
Joan Jonathan, Alcardo Alex Barakabitze, Cynthia D Fast, Christophe Cox
BACKGROUND: Technological advancement has led to the growth and rapid increase of tuberculosis (TB) medical data generated from different health care areas, including diagnosis. Prioritizing better adoption and acceptance of innovative diagnostic technology to reduce the spread of TB significantly benefits developing countries. Trained TB-detection rats are used in Tanzania and Ethiopia for operational research to complement other TB diagnostic tools. This technology has increased new TB case detection owing to its speed, cost-effectiveness, and sensitivity...
April 16, 2024: Online Journal of Public Health Informatics
#24
JOURNAL ARTICLE
Kate J Wahl, Melissa Brooks, Logan Trenaman, Kirsten Desjardins-Lorimer, Carolyn M Bell, Nazgul Chokmorova, Romy Segall, Janelle Syring, Aleyah Williams, Linda C Li, Wendy V Norman, Sarah Munro
BACKGROUND: People seeking abortion in early pregnancy have the choice between medication and procedural options for care. The choice is preference-sensitive-there is no clinically superior option and the choice depends on what matters most to the individual patient. Patient decision aids (PtDAs) are shared decision-making tools that support people in making informed, values-aligned health care choices. OBJECTIVE: We aimed to develop and evaluate the usability of a web-based PtDA for the Canadian context, where abortion care is publicly funded and available without legal restriction...
April 16, 2024: Journal of Medical Internet Research
#25
JOURNAL ARTICLE
Satoshi Nishioka, Satoshi Watabe, Yuki Yanagisawa, Kyoko Sayama, Hayato Kizaki, Shungo Imai, Mitsuhiro Someya, Ryoo Taniguchi, Shuntaro Yada, Eiji Aramaki, Satoko Hori
BACKGROUND: Early detection of adverse events and their management are crucial to improving anticancer treatment outcomes, and listening to patients' subjective opinions (patients' voices) can make a major contribution to improving safety management. Recent progress in deep learning technologies has enabled various new approaches for the evaluation of safety-related events based on patient-generated text data, but few studies have focused on the improvement of real-time safety monitoring for individual patients...
April 16, 2024: Journal of Medical Internet Research
#26
JOURNAL ARTICLE
Ying Wang, Yanling Chen, Yuqing Song, Hong Chen, Xin Guo, Ling Ma, Huan Liu
BACKGROUND: In patients with gout, suboptimal management refers to a lack of disease knowledge, low treatment compliance, and inadequate control of serum uric acid (SUA) levels. Several studies have shown that continuous care is recommended for disease management in patients with gout. However, in China, the continuous care model commonly used for patients with gout requires significant labor and time costs, and its efficiency and coverage remain low. Mobile health (mHealth) may be able to address these issues...
April 11, 2024: JMIR MHealth and UHealth
#27
JOURNAL ARTICLE
Lachlan Lee, Rosemary Hall, James Stanley, Jeremy Krebs
BACKGROUND: Accurately assessing an individual's diet is vital in the management of personal nutrition and in the study of the effect of diet on health. Despite its importance, the tools available for dietary assessment remain either too imprecise, expensive, or burdensome for clinical or research use. Image-based methods offer a potential new tool to improve the reliability and accessibility of dietary assessment. Though promising, image-based methods are sensitive to adherence, as images cannot be captured from meals that have already been consumed...
April 15, 2024: JMIR MHealth and UHealth
#28
JOURNAL ARTICLE
Onkar Litake, Brian H Park, Jeffrey L Tully, Rodney A Gabriel
OBJECTIVES: To compare performances of a classifier that leverages language models when trained on synthetic versus authentic clinical notes. MATERIALS AND METHODS: A classifier using language models was developed to identify acute renal failure. Four types of training data were compared: (1) notes from MIMIC-III; and (2, 3, and 4) synthetic notes generated by ChatGPT of varied text lengths of 15 (GPT-15 sentences), 30 (GPT-30 sentences), and 45 (GPT-45 sentences) sentences, respectively...
April 15, 2024: Journal of the American Medical Informatics Association: JAMIA
#29
JOURNAL ARTICLE
Cathy Shyr, Lina Sulieman, Paul A Harris
OBJECTIVE: With its size and diversity, the All of Us Research Program has the potential to power and improve representation in clinical trials through ancillary studies like Nutrition for Precision Health. We sought to characterize high-level trial opportunities for the diverse participants and sponsors of future trial investment. MATERIALS AND METHODS: We matched All of Us participants with available trials on ClinicalTrials.gov based on medical conditions, age, sex, and geographic location...
April 15, 2024: Journal of the American Medical Informatics Association: JAMIA
#30
JOURNAL ARTICLE
Catarina Martins, Bernardo Neves, Andreia Sofia Teixeira, Miguel Froes, Pedro Sarmento, Jaime Machado, Carlos A Magalhães, Nuno A Silva, Mário J Silva, Francisca Leite
This study presents a workflow for identifying and characterizing patients with Heart Failure (HF) and multimorbidity utilizing data from Electronic Health Records. Multimorbidity, the co-occurrence of two or more chronic conditions, poses a significant challenge on healthcare systems. Nonetheless, understanding of patients with multimorbidity, including the most common disease interactions, risk factors, and treatment responses, remains limited, particularly for complex and heterogeneous conditions like HF...
April 15, 2024: BMC Medical Informatics and Decision Making
#31
JOURNAL ARTICLE
Xinwei Zhao, Junqing Xu, Youyuan Shui, Mengdie Xu, Jie Hu, Xiaoyan Liu, Kai Che, Junjie Wang, Yun Liu
MOTIVATION: Drug combination therapies have shown promise in clinical cancer treatments. However, it is hard to experimentally identify all drug combinations for synergistic interaction even with high-throughput screening due to the vast space of potential combinations. Although a number of computational methods for drug synergy prediction have proven successful in narrowing down this space, fusing drug pairs and cell line features effectively still lacks study, hindering current algorithms from understanding the complex interaction between drugs and cell lines...
April 15, 2024: Journal of Cheminformatics
#32
JOURNAL ARTICLE
Pinar Tokgöz, Stephan Krayter, Jessica Hafner, Christoph Dockweiler
BACKGROUND: Inappropriate antimicrobial use, such as antibiotic intake in viral infections, incorrect dosing and incorrect dosing cycles, has been shown to be an important determinant of the emergence of antimicrobial resistance. Artificial intelligence-based decision support systems represent a potential solution for improving antimicrobial prescribing and containing antimicrobial resistance by supporting clinical decision-making thus optimizing antibiotic use and improving patient outcomes...
April 15, 2024: BMC Medical Informatics and Decision Making
#33
JOURNAL ARTICLE
Anlin Luo, Shuiping Gou, Nuo Tong, Bo Liu, Licheng Jiao, Hu Xu, Yingchun Wang, Tan Ding
Meniscal injury represents a common type of knee injury, accounting for over 50% of all knee injuries. The clinical diagnosis and treatment of meniscal injury heavily rely on magnetic resonance imaging (MRI). However, accurately diagnosing the meniscus from a comprehensive knee MRI is challenging due to its limited and weak signal, significantly impeding the precise grading of meniscal injuries. In this study, a visual interpretable fine grading (VIFG) diagnosis model has been developed to facilitate intelligent and quantified grading of meniscal injuries...
April 15, 2024: NPJ Digital Medicine
#34
JOURNAL ARTICLE
Zehao Yu, Cheng Peng, Xi Yang, Chong Dang, Prakash Adekkanattu, Braja Gopal Patra, Yifan Peng, Jyotishman Pathak, Debbie L Wilson, Ching-Yuan Chang, Wei-Hsuan Lo-Ciganic, Thomas J George, William R Hogan, Yi Guo, Jiang Bian, Yonghui Wu
OBJECTIVE: To develop a natural language processing (NLP) package to extract social determinants of health (SDoH) from clinical narratives, examine the bias among race and gender groups, test the generalizability of extracting SDoH for different disease groups, and examine population-level extraction ratio. METHODS: We developed SDoH corpora using clinical notes identified at the University of Florida (UF) Health. We systematically compared 7 transformer-based large language models (LLMs) and developed an open-source package - SODA (i...
April 13, 2024: Journal of Biomedical Informatics
#35
JOURNAL ARTICLE
Khushboo Teotia, Yueran Jia, Naira Link Woite, Leo Anthony Celi, João Matos, Tristan Struja
OBJECTIVE: Health inequities can be influenced by demographic factors such as race and ethnicity, proficiency in English, and biological sex. Disparities may manifest as differential likelihood of testing which correlates directly with the likelihood of an intervention to address an abnormal finding. Our retrospective observational study evaluated the presence of variation in glucose measurements in the Intensive Care Unit (ICU). METHODS: Using the MIMIC-IV database (2008-2019), a single-center, academic referral hospital in Boston (USA), we identified adult patients meeting sepsis-3 criteria...
April 13, 2024: Journal of Biomedical Informatics
#36
JOURNAL ARTICLE
Margarita L Zuley, Jonathan Silverstein, Durwin Logue, Richard S Morgan, Rohit Bhargava, Priscilla F McAuliffe, Adam M Brufsky, Andriy I Bandos, Robert M Nishikawa
PURPOSE: In the United States, a comprehensive national breast cancer registry (CR) does not exist. Thus, care and coverage decisions are based on data from population subsets, other countries, or models. We report a prototype real-world research data mart to assess mortality, morbidity, and costs for breast cancer diagnosis and treatment. METHODS: With institutional review board approval and Health Insurance Portability and Accountability Act (HIPPA) compliance, a multidisciplinary clinical and research data warehouse (RDW) expert group curated demographic, risk, imaging, pathology, treatment, and outcome data from the electronic health records (EHR), radiology (RIS), and CR for patients having breast imaging and/or a diagnosis of breast cancer in our institution from January 1, 2004, to December 31, 2020...
April 2024: JCO Clinical Cancer Informatics
#37
JOURNAL ARTICLE
R Gentry Wilkerson, Youssef Annous, Eli Farhy, Jonathan Hurst, Angela D Smedley
OBJECTIVES: Patients with suspected COVID-19 remain at risk for clinical deterioration after discharge and may benefit from home oxygen saturation (SpO2 ) monitoring using portable pulse oximeter devices. Our study aims to evaluate patient engagement and compliance with a home SpO2 monitoring program. METHODS: This is a single center, prospective pilot study of patients being discharged from the ED or urgent care after evaluation of symptoms consistent with COVID-19...
June 26, 2023: Health Policy and Technology
#38
JOURNAL ARTICLE
Meghan R Hutch, Jiyeon Son, Trang T Le, Chuan Hong, Xuan Wang, Zahra Shakeri Hossein Abad, Michele Morris, Alba Gutiérrez-Sacristán, Jeffrey G Klann, Anastasia Spiridou, Ashley Batugo, Riccardo Bellazzi, Vincent Benoit, Clara-Lea Bonzel, William A Bryant, Lorenzo Chiudinelli, Kelly Cho, Priyam Das, Tomás González González, David A Hanauer, Darren W Henderson, Yuk-Lam Ho, Ne Hooi Will Loh, Adeline Makoudjou, Simran Makwana, Alberto Malovini, Bertrand Moal, Danielle L Mowery, Antoine Neuraz, Malarkodi Jebathilagam Samayamuthu, Fernando J Sanz Vidorreta, Emily R Schriver, Petra Schubert, Jeffery Talbert, Amelia L M Tan, Byorn W L Tan, Bryce W Q Tan, Valentina Tibollo, Patric Tippman, Guillaume Verdy, William Yuan, Paul Avillach, Nils Gehlenborg, Gilbert S Omenn, Shyam Visweswaran, Tianxi Cai, Yuan Luo, Zongqi Xia
Few studies examining the patient outcomes of concurrent neurological manifestations during acute COVID-19 leveraged multinational cohorts of adults and children or distinguished between central and peripheral nervous system (CNS vs. PNS) involvement. Using a federated multinational network in which local clinicians and informatics experts curated the electronic health records data, we evaluated the risk of prolonged hospitalization and mortality in hospitalized COVID-19 patients from 21 healthcare systems across 7 countries...
April 2024: PLOS Digit Health
#39
JOURNAL ARTICLE
Matthew Trunnell, Casey Frankenberger, Bala Hota, Troy Hughes, Plamen Martinov, Urmila Ravichandran, Nirav S Shah, Robert L Grossman
OBJECTIVES: A data commons is a software platform for managing, curating, analyzing, and sharing data with a community. The Pandemic Response Commons (PRC) is a data commons designed to provide a data platform for researchers studying an epidemic or pandemic. METHODS: The PRC was developed using the open source Gen3 data platform and is based upon consortium, data, and platform agreements developed by the not-for-profit Open Commons Consortium. A formal consortium of Chicagoland area organizations was formed to develop and operate the PRC...
July 2024: JAMIA Open
#40
JOURNAL ARTICLE
Xiaoyu Wang, Yao Lin, Zheng Li, Yueqi Li, Mingcong Chen
BACKGROUND: Alternative polyadenylation (APA) plays a vital regulatory role in various diseases. It is widely accepted that APA is regulated by APA regulatory factors. OBJECTIVE: Whether APA regulatory factors affect the prognosis of renal cell carcinoma remains unclear, and this is the main topic of this study. METHODS: We downloaded the transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database. We used the Lasso regression system to construct an APA model for analyzing the relationship between common APA regulatory factors and renal cell carcinoma...
2024: Cancer Informatics
Make the most of Read.
Download the mobile app.
Download the mobile app.
Fetching more papers... 
