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ORCIDInternational Journal of Medical Informatics, Volume 196
Volume 196, 2025
- Shan Chen
, Yuanzhao Ding:
The feasibility of using machine learning to predict COVID-19 cases. 105786 - Hassan Bozorgmanesh, Patrik Rydén:
Optimal placement of ambulance stations using data-driven direct and surrogate search methods. 105790 - Catherine Smallwood, Carlos Matos, Hugo Monteiro, Mark Shapiro, Miranda Tran Ngoc, Mohamed Elamein, Raviv Raz, Samuel Petragallo:
Enhancing information for action: A strategic tool for strengthening public health emergency management systems. 105791 - Mengying Li, Yin Fang, Jiong Shao, Yan Jiang, Guoping Xu, Xin-wu Cui, Xinglong Wu:
Vision transformer-based multimodal fusion network for classification of tumor malignancy on breast ultrasound: A retrospective multicenter study. 105793 - Simon Lewerenz, Anne Moen, Henrique Martins:
Public value and digital health: The example of guiding values in the national digital health strategy of France. 105794 - Renata Savian Colvero de Oliveira, Sharon Nabwire, Heta Merikallio, Markku J. Savolainen, Janne Hukkanen, Harri Oinas-Kukkonen:
Behind the software: The impact of Unobtrusiveness, Goal Setting and persuasive features on BMI. 105795 - Liqin Wang, John Laurentiev, Claire Cook, Shruthi Srivatsan, Yining Hua, Jie Yang, Eli Miloslavsky, Hyon K. Choi, Li Zhou, Zachary S. Wallace:
Identification of an ANCA-associated vasculitis cohort using deep learning and electronic health records. 105797 - Wei Feng, Honghan Wu, Hui Ma, Yuechuchu Yin, Zhenhuan Tao, Shan Lu, Xin Zhang, Yun Yu, Cheng Wan, Yun Liu:
Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records. 105801 - Francesco Masciulli, Anna Corti, Alessia Lindemann, Katia Chiappetta, Mattia Loppini, Valentina D. A. Corino:
Hip prosthesis failure prediction through radiological deep sequence learning. 105802 - Jon Urteaga, Andoni Elola, Daniel Herráez, Anders Norvik, Eirik Unneland, Abhishek Bhardwaj, David Buckler, Benjamin S. Abella, Eirik Skogvoll, Elisabete Aramendi:
A deep learning model for QRS delineation in organized rhythms during in-hospital cardiac arrest. 105803 - Sharareh Rostam Niakan Kalhori, Farid Najafi, Hajar Hasannejadasl, Soroush Heydari:
Artificial intelligence-enabled obesity prediction: A systematic review of cohort data analysis. 105804 - Yookyung Boo, YoungJin Choi:
A comparative analysis of trauma-related mortality in South Korea using classification models. 105805 - Chen Chen, Wenkang Zhang, Yang Pan, Zhen Li:
An interpretable hybrid machine learning approach for predicting three-month unfavorable outcomes in patients with acute ischemic stroke. 105807 - Jiqing Li, Shuo Wu, Jianhua Gu:
Explainable machine learning model for assessing health status in patients with comorbid coronary heart disease and depression: Development and validation study. 105808 - Milad Ghiasi Rad, Alireza Rafiei, Jocelyn Grunwell, Rishikesan Kamaleswaran:
Tackling the small imbalanced horizontal dataset regressions by Stability Selection and SMOGN: a case study of ventilation-free days prediction in the pediatric intensive care unit and the importance of PRISM. 105809 - Maria Alejandra Pinero De Plaza, Kristina Lambrakis, Fernando Marmolejo-Ramos, Alline M. R. Beleigoli, Mandy Archibald, Lalit Yadav, Penelope McMillan, Robyn Clark, Michael Lawless, Erin Morton, Jeroen Hendriks, Alison Kitson, Renuka Visvanathan, Derek P. Chew, Carlos Javier Barrera Causil:
Human-centred AI for emergency cardiac care: Evaluating RAPIDx AI with PROLIFERATE_AI. 105810 - William Heseltine-Carp, Megan Courtman, Daniel Browning, Aishwarya Kasabe, Michael Allen, Adam Streeter, Emmanuel C. Ifeachor, Martin James, Stephen Mullin:
Machine learning to predict stroke risk from routine hospital data: A systematic review. 105811 - Qian Wu, Hui Guo, Ruihan Li, Jinhuan Han:
Deep learning and machine learning in CT-based COPD diagnosis: Systematic review and meta-analysis. 105812 - Shan Li, Jinkui Wang, Zhaoxia Zhang, Chunnian Ren, Dawei He:
Individual risk and prognostic value prediction by interpretable machine learning for distant metastasis in neuroblastoma: A population-based study and an external validation. 105813 - Tinja Lääveri, Päivi Metsäniemi, Timo Tuovinen, Suvi Vainiomäki, Jarmo Reponen:
Healthcare information system support for leadership and management: Experiences of Finnish physician leaders by specialty from three cross-sectional surveys in 2014, 2017, and 2021. 105814 - R. van Slobbe, D. Herrmannova, D. J. Boeke, Elia Lima-Walton, Ameen Abu-Hanna, Iacopo Vagliano:
Multimodal convolutional neural networks for the prediction of acute kidney injury in the intensive care. 105815 - Yashpal Ramakrishnaiah, Nenad Macesic, Geoffrey I. Webb, Anton Y. Peleg, Sonika Tyagi:
EHR-ML: A data-driven framework for designing machine learning applications with electronic health records. 105816 - Yun Woo Lee, Ji-Hun Kim, Jin Ju Park, Hyejin Park, Hyeonji Seo, Yong Kyun Kim:
Development and external validation of a machine learning model to predict the initial dose of vancomycin for targeting an area under the concentration-time curve of 400-600 mg∙h/L. 105817 - Ling Zhang, Robyn Gallagher, Huiyun Du, Tracey Barry, Jon Foote, Tiffany Ellis, Aarti Gulyani, Robyn A. Clark:
Evaluate the effect of virtual nurse-guided discharge education app on disease knowledge and symptom response in patients following coronary events. 105818 - Elisa Ambrosi, Elisabetta Mezzalira, Federica Canzan, Chiara Leardini, Giovanni Vita, Giulia Marini, Jessica Longhini:
Effectiveness of digital health interventions for chronic conditions management in European primary care settings: Systematic review and meta-analysis. 105820 - Serena Daniel, Ruth Bishop, Ellie Killner, Alison Whight, Sarah Lennard, Stephen Howard, Richard Laugharne, Rohit Shankar:
Serious Games for constipation management for people with intellectual disabilities: A scoping review and narrative synthesis. 105832 - Hisrael Passarelli-Araujo:
Exploring the importance of clinical and sociodemographic factors on self-rated health in midlife: A cross-sectional study using machine learning. 105834
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