Article
Medical Informatics
Tariku Nigatu Bogale, Herman Willems, Loko Abraham Bongassie, Yemariam Eyob, Chaluma Kumela Mengesha, Bantalem Yeshanew Yihun, Mesud Mohammed, Naod Wendrad, Gemechis Melkamu, Dawit Wolde Daka, Selamawit Meressa, Tadesse Alemu Bekele
Summary: This study assessed the acceptability and use of the electronic community health information system among health extension workers in Ethiopia. The results showed that while there was near universal acceptance of the system, actual use was considerably lower. Perceived usefulness and ease of use were found to significantly impact acceptability, which in turn had a positive effect on usage.
BMC MEDICAL INFORMATICS AND DECISION MAKING
(2023)
Article
Mathematical & Computational Biology
Dan Jackson, Wolfgang Viechtbauer, Robbie C. M. van Aert
Summary: This paper investigates methods for estimating the between-study variance in a multivariate setting. By extending the univariate generalized method of moments, a wider class of multivariate methods is obtained. The main proposal is to use this new type of estimator to derive multivariate multistep estimators of the between-study covariance matrix. The research finds that the proposed methodology is a fully viable alternative to existing estimation methods, particularly in application areas where data are expected to be heterogeneous.
STATISTICS IN MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Bommala Silpa, Malaya Kumar Hota
Summary: This research proposes an optimized VME-REG algorithm to detect eye blink artifacts in EEG recordings and tests it on multiple datasets, demonstrating improved performance compared to existing methods.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2023)
Article
Mathematical & Computational Biology
Yuelin Lu, Bradley P. Carlin, John W. Seaman Jr
Summary: This study focuses on Bayesian inference to predict survival probabilities in the development of an Ebola vaccine using a prime-boost vaccination regime. Two models are established to determine the relationship between dose concentration and induced antibody count, as well as the association between antibody count and probability of survival. The research offers a new application of drug synergy models for prime-boost vaccine efficacy.
STATISTICS IN MEDICINE
(2023)
Article
Computer Science, Information Systems
Anjun Chen, Drake O. Chen, Lu Tian
Summary: This study evaluates the symptom-checking accuracy of ChatGPT for a broad range of diseases using the Mayo Clinic Symptom Checker patient service as a benchmark. The results show that ChatGPT exhibits high accuracy, surpassing the previous GPT-3.5-turbo model, and demonstrating its potential as a medical training tool in learning health systems to enhance care quality and address health disparities.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Article
Medical Informatics
Guanghui Li, Feifan Zeng, Jiawei Luo, Cheng Liang, Qiu Xiao
Summary: CircRNAs play a crucial role in drug resistance and cancer development, and the development of an efficient computational method to predict the associations between drug sensitivity and circRNAs is of great importance.
BMC MEDICAL INFORMATICS AND DECISION MAKING
(2023)
Review
Medical Informatics
Shumin Ren, Jiakun Li, Julian Dorado, Alejandro Sierra, Humbert Gonzalez-Diaz, Aliuska Duardo, Bairong Shen
Summary: Prostate cancer is a complex and heterogeneous disease that poses challenges in treatment. Issues such as overtreatment, limited metastasis and dormant tumor recognition, and personalized drug utilization need attention. Integrating multidimensional data can help identify molecular subtypes, predict cancer progression, and enable personalized treatment. Artificial intelligence and machine learning techniques are valuable for processing extensive data and uncovering potential patterns and insights.
HEALTH INFORMATION SCIENCE AND SYSTEMS
(2023)
Article
Health Care Sciences & Services
Marijn Muurling, Casper de Boer, Srinivasan Vairavan, Robbert L. Harms, Antonella Santuccione Chadha, Ioannis Tarnanas, Estefania Vilarino Luis, Dorota Religa, Martha Therese Gjestsen, Samantha Galluzzi, Marta Ibarria Sala, Ivan Koychev, Lucrezia Hausner, Mara Gkioka, Dag Aarsland, Pieter Jelle Visser, Anna-Katharine Brem
Summary: This study successfully distinguished early Alzheimer's disease patients from healthy controls using an augmented reality (AR) app, both in clinical and home settings. The digital score from the app showed good classification accuracy and was associated with clinical cognitive scores. These findings demonstrate the feasibility and effectiveness of using AR for cognitive measurements in Alzheimer's disease.
NPJ DIGITAL MEDICINE
(2023)
Review
Medical Informatics
Nicola Antognini, Ronald Portman, Victor Dong, Nicholas J. Webb, Deepa H. Chand
Summary: The kidneys play a crucial role in drug elimination, making it vital for those involved in drug development to have a comprehensive understanding of renal physiology and pathology. Drug-induced nephrotoxicity (DIN) can be difficult to identify, as it may occur against a backdrop of pre-existing renal impairment. The development of novel biomarkers can aid in the early and accurate diagnosis of kidney damage caused by drugs.
THERAPEUTIC INNOVATION & REGULATORY SCIENCE
(2023)
Article
Mathematical & Computational Biology
Chao Yang, Yisheng Li
Summary: We propose a model-based, semi-mechanistic dose-finding (SDF) design that incorporates pharmacokinetic/pharmacodynamic (PK/PD) information when modeling the dose-toxicity relationship. This design outperforms common phase I trial designs in terms of selecting the maximum tolerated dose (MTD) and allocating patients to MTD. By jointly modeling PK, PD, and dose-limiting toxicity (DLT) outcomes using Bayesian methods, the proposed design yields better estimated dose-toxicity curves and is robust to certain model specifications.
STATISTICS IN MEDICINE
(2023)
Review
Health Care Sciences & Services
Sherry On Ki Chong, Sara Pedron, Nancy Abdelmalak, Michael Laxy, Anna-Janina Stephan
Summary: Health interventions based on mobile apps show promise in helping patients manage their conditions. This umbrella review summarizes systematic reviews on the efficacy and effectiveness of mobile app-based health interventions in patient populations. The findings indicate varying effectiveness across different indications. Future research should focus on reporting behavioral outcomes and healthcare resource utilization to better understand the mechanisms and impact of health apps on healthcare systems.
NPJ DIGITAL MEDICINE
(2023)
Article
Medical Informatics
Maryam Karami, Hossein Ashtarian, Mojgan Rajati, Behrooz Hamzeh, Fatemeh Rajati
Summary: Intervention using programmed instruction through M-Health significantly improved the health literacy and medication adherence of uncontrolled hypertensive patients. The intervention group showed a significant increase in medication adherence score, as well as reductions in both systolic and diastolic blood pressure.
BMC MEDICAL INFORMATICS AND DECISION MAKING
(2023)
Article
Health Care Sciences & Services
Christine Jacob, Johan Lindeque, Roman Mueller, Alexander Klein, Thomas Metcalfe, Samantha L. Connolly, Florian Koerber, Roma Maguire, Fabrice Denis, Sabina C. Heuss, Marc K. Peter
Summary: This study validates and refines a list of 55 assessment criteria for eHealth tools through a two-round modified Delphi process. The criteria are classified into foundational and contextual, allowing for evaluation of both the quality of the tool and its suitability in a specific setting.
NPJ DIGITAL MEDICINE
(2023)
Article
Computer Science, Information Systems
Heath A. Davis, Donna A. Santillan, Chris E. Ortman, Asher A. Hoberg, Joseph P. Hetrick, Charles W. Mcbrearty, Erliang Zeng, Mary S. Vaughan Sarrazin, Karen Dunn Lopez, Cole G. Chapman, Ryan M. Carnahan, Jacob J. Michaelson, Boyd M. Knosp
Summary: This manuscript describes the objectives and methods of the Iowa Health Data Resource (IHDR). IHDR is a strategic investment made by the University of Iowa to improve access to real-world health data and enhance translational health research.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Mansour Ashoor, Abdollah Khorshidi
Summary: In medical imaging, the signal to noise ratio (SNR) is crucial for displaying image details. This study proposes a new function that combines the longitudinal and transverse magnetization components to improve the SNR of images. The method can be applied to any medical images and offers the potential for optimizing MRI techniques.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2023)
Article
Mathematical & Computational Biology
C. S. Davila-Payan, A. Hill, L. Kayembe, J. P. Alexander, M. Lynch, S. W. Pallas
Summary: This study introduces a novel approach to formulate vaccine schedules for different age groups, taking into account the effects of vaccination age, timing, and disease seasonality on disease incidence. The methodology also adjusts for the temporal interaction between vaccination and disease exposure, increasing population immunity.
STATISTICS IN MEDICINE
(2023)
Article
Mathematical & Computational Biology
Elizabeth C. Chase, Jeremy M. G. Taylor, Philip S. Boonstra
Summary: Biomedical data often exhibit jumps or abrupt changes, such as women's basal body temperature. These sudden changes make modeling challenging, and we have developed a method called horseshoe process regression to address this problem.
STATISTICS IN MEDICINE
(2023)
Letter
Health Care Sciences & Services
Natalia Kunst, Annisa Siu, Michael Drummond, Sabine Grimm, Janneke Grutters, Don Husereau, Hendrik Koffijberg, Claire Rothery, Edward C. F. Wilson, Anna Heath
MEDICAL DECISION MAKING
(2023)
Article
Computer Science, Interdisciplinary Applications
Yanxia Liu, Xiaozhen Li, Rui Li, SiJuan Huang, Xin Yang
Summary: Image registration of MRI pre- and post-therapy is crucial for evaluating the effectiveness of tumor treatment. Existing methods using single-view data for registration can be misled by erroneous spatial information in blurred regions. This paper proposes a multi-stream fusion-assisted registration network that utilizes different-view MRIs and a cross-attention guided fusion module to enhance the accuracy of MRI image registration before and after radiotherapy.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2023)
Article
Computer Science, Information Systems
Amelia K. Barwise, Susan Curtis, Daniel A. Diedrich, Brian W. Pickering
Summary: Using machine learning predictive analytics to identify and prioritize patients with language barriers and complex medical needs for interpreter services has the potential to improve healthcare disparities and provide better quality of care.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
