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  1. The use of remote services such as video consultations (VCs) has increased significantly in the wake of the COVID-19 pandemic. In Sweden, private healthcare providers offering VCs have grown substantially sinc...

    Authors: Maria Hägglund, Anna Kristensson Ekwall, Nadia Davoody and Nasim Farrokhnia
    Citation: BMC Medical Informatics and Decision Making 2023 23:231
  2. IMPACT-AF is a prospective, randomized, cluster design trial comparing atrial fibrillation (AF) management with a computerized decision support system (CDS) to usual care (control) in the primary care setting ...

    Authors: Brittany Humphries, Jafna L Cox, Ratika Parkash, Lehana Thabane, Gary A Foster, James MacKillop, Joanna Nemis-White, Laura Hamilton, Antonio Ciaccia, Shurjeel H Choudhri, Bruno Kovic and Feng Xie
    Citation: BMC Medical Informatics and Decision Making 2023 23:228
  3. Thermoregulation is important for all age groups, and in neonates, it is considered a crucial event to adapt to extrauterine life. Therefore, using systems that provide frequent reminders in different ways in ...

    Authors: Raziyeh Beykmirza, Elahe Rastkar Mehrabani, Maryam Hashemi, Maryam Mahdizade Shahri, Reza Negarandeh and Maryam Varzeshnejad
    Citation: BMC Medical Informatics and Decision Making 2023 23:227
  4. Computerized clinical decision support systems (CDSSs) can improve care by bridging knowledge to practice gaps. However, the real-world uptake of such systems in health care settings has been suboptimal. We so...

    Authors: Janet Yamada, Andrew Kouri, Sarah Nicole Simard, Jeffrey Lam Shin Cheung, Stephanie Segovia and Samir Gupta
    Citation: BMC Medical Informatics and Decision Making 2023 23:226
  5. Saliency-based algorithms are able to explain the relationship between input image pixels and deep-learning model predictions. However, it may be difficult to assess the clinical value of the most important im...

    Authors: Michael Osadebey, Qinghui Liu, Elies Fuster-Garcia and Kyrre E. Emblem
    Citation: BMC Medical Informatics and Decision Making 2023 23:225
  6. For surveillance of episodic illness, the emergency department (ED) represents one of the largest interfaces for generalizable data about segments of the US public experiencing a need for unscheduled care. Thi...

    Authors: Jeffrey A. Kline, Brian Reed, Alex Frost, Naomi Alanis, Meylakh Barshay, Andrew Melzer, James W. Galbraith, Alicia Budd, Amber Winn, Eugene Pun and Carlos A. Camargo Jr.
    Citation: BMC Medical Informatics and Decision Making 2023 23:224
  7. Women with pathogenic BRCA1 or BRCA2 variants are at high risk for breast and ovarian cancer. Preventive options include risk-reducing breast and ovarian surgeries and intensified breast surveillance. However, in...

    Authors: Sibylle Kautz-Freimuth, Marcus Redaèlli, Arim Shukri, Hannah Kentenich, Dusan Simic, Vanessa Mildenberger, Rita Schmutzler, Kerstin Rhiem and Stephanie Stock
    Citation: BMC Medical Informatics and Decision Making 2023 23:223
  8. With the development of big health and big data, cohort research has become a medical research hotspot. As an important repository of human genetic resources, biobanks must adapt to the requirements of large-s...

    Authors: Lianshuai Zheng and Leilei Wang
    Citation: BMC Medical Informatics and Decision Making 2023 23:222
  9. This article focuses on the development of algorithms for a smart neurorehabilitation system, whose core is made up of artificial neural networks. The authors of the article have proposed a completely unique t...

    Authors: Martin Kotyrba, Hashim Habiballa, Eva Volna, Robert Jarusek, Pavel Smolka, Martin Prasek, Marek Malina and Vladena Jaremova
    Citation: BMC Medical Informatics and Decision Making 2023 23:221
  10. Primary care electronic health records (EHR) are widely used to study long-term conditions in epidemiological and health services research. Therefore, it is important to understand how well the recorded preval...

    Authors: Jennifer Cooper, Krishnarajah Nirantharakumar, Francesca Crowe, Amaya Azcoaga-Lorenzo, Colin McCowan, Thomas Jackson, Aditya Acharya, Krishna Gokhale, Niluka Gunathilaka, Tom Marshall and Shamil Haroon
    Citation: BMC Medical Informatics and Decision Making 2023 23:220
  11. With population aging and the scarcity of resources for elderly individuals, wearable devices pose opportunities and challenges for elderly care institutions. However, few studies have examined the effects of ...

    Authors: Ying Wang, Liyan Lu, Rui Zhang, Yiming Ma, Shuping Zhao and Changyong Liang
    Citation: BMC Medical Informatics and Decision Making 2023 23:218
  12. Important clinical information of patients is present in unstructured free-text fields of Electronic Health Records (EHRs). While this information can be extracted using clinical Natural Language Processing (c...

    Authors: Guillermo Argüello-González, José Aquino-Esperanza, Daniel Salvador, Rosa Bretón-Romero, Carlos Del Río-Bermudez, Jorge Tello and Sebastian Menke
    Citation: BMC Medical Informatics and Decision Making 2023 23:216
  13. The most prevalent mesenchymal-derived gastrointestinal cancers are gastric stromal tumors (GSTs), which have the highest incidence (60–70%) of all gastrointestinal stromal tumors (GISTs). However, simple and ...

    Authors: Shangjun Han, Meijuan Song, Jiarui Wang, Yalong Huang, Zuxi Li, Aijia Yang, Changsheng Sui, Zeping Zhang, Jiling Qiao and Jing Yang
    Citation: BMC Medical Informatics and Decision Making 2023 23:214
  14. This study intends to build an artificial intelligence model for obstetric cesarean section surgery to evaluate the intraoperative blood transfusion volume before operation, and compare the model prediction re...

    Authors: Hang Chen, Bowei Cao, Jiangcun Yang, He Ren, Xingqiu Xia, Xiaowen Zhang, Wei Yan, Xiaodan Liang and Chen Li
    Citation: BMC Medical Informatics and Decision Making 2023 23:213
  15. Investment in the implementation of hospital ePrescribing systems has been a priority in many economically-developed countries in order to modernise the delivery of healthcare. However, maximum gains in the sa...

    Authors: Catherine Heeney, Matt Bouamrane, Stephen Malden, Kathrin Cresswell, Robin Williams and Aziz Sheikh
    Citation: BMC Medical Informatics and Decision Making 2023 23:211
  16. Electronic medical records (EMRs) contain a wealth of information related to breast cancer diagnosis and treatment. Extracting relevant features from these medical records and constructing a knowledge graph ca...

    Authors: Xiaolong Li, Shuifa Sun, Tinglong Tang, Ji Lu, Lijuan Zhang, Jie Yin, Qian Geng and Yirong Wu
    Citation: BMC Medical Informatics and Decision Making 2023 23:210
  17. In the modern era of antibiotics, healthcare-associated infections (HAIs) have emerged as a prominent and concerning health threat worldwide. Implementing an electronic surveillance system for healthcare-assoc...

    Authors: Yu Cao, Yaojun Niu, Xuetao Tian, DeZhong Peng, Li Lu and Haojun Zhang
    Citation: BMC Medical Informatics and Decision Making 2023 23:209
  18. Clinical events suggestive of nutrition care found in electronic health records (EHRs) are rarely explored for their associations with hypertension outcomes.

    Authors: April R. Williams, Maria D. Thomson and Erin L. Britton
    Citation: BMC Medical Informatics and Decision Making 2023 23:208
  19. There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of incon...

    Authors: Amir Kamel Rahimi, Moji Ghadimi, Anton H. van der Vegt, Oliver J. Canfell, Jason D. Pole, Clair Sullivan and Sally Shrapnel
    Citation: BMC Medical Informatics and Decision Making 2023 23:207
  20. Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient’s condition and deciding on transport destinatio...

    Authors: Anna Bakidou, Eva-Corina Caragounis, Magnus Andersson Hagiwara, Anders Jonsson, Bengt Arne Sjöqvist and Stefan Candefjord
    Citation: BMC Medical Informatics and Decision Making 2023 23:206
  21. This research aims to develop a diagnostic tool that can quickly and accurately detect prostate cancer using electronic nose technology and a neural network trained on a dataset of urine samples from patients ...

    Authors: J. B. Talens, J. Pelegri-Sebastia, T. Sogorb and J. L. Ruiz
    Citation: BMC Medical Informatics and Decision Making 2023 23:205
  22. Medical crowdsourcing competitions can help patients get more efficient and comprehensive treatment advice than “one-to-one” service, and doctors should be encouraged to actively participate. In the crowdsourc...

    Authors: Xiuxiu Zhou, Shanshan Guo and Hong Wu
    Citation: BMC Medical Informatics and Decision Making 2023 23:204
  23. Given the increasing number of dementia patients worldwide, a new method was developed for machine learning models to identify the ‘latent needs’ of patients and caregivers to facilitate patient/public involve...

    Authors: Nanae Tanemura, Tsuyoshi Sasaki, Ryotaro Miyamoto, Jin Watanabe, Michihiro Araki, Junko Sato and Tsuyoshi Chiba
    Citation: BMC Medical Informatics and Decision Making 2023 23:203
  24. Menopause is a normal transition in a woman’s life. For some women, it is a stage without significant difficulties; for others, menopause symptoms can severely affect their quality of life. This study develope...

    Authors: Anh N.Q. Pham, Michael Cummings, Nese Yuksel, Beate Sydora, Tyler Williamson, Stephanie Garies, Russell Pilling, Cliff Lindeman and Sue Ross
    Citation: BMC Medical Informatics and Decision Making 2023 23:202

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2023 23:233

  25. Obesity is a multifaceted condition that impacts individuals across various age, racial, and socioeconomic demographics, hence rendering them susceptible to a range of health complications and an increased ris...

    Authors: Zahra Zare, Elmira Hajizadeh, Maryam Mahmoodi, Reza Nazari, Leila Shahmoradi and Sorayya Rezayi
    Citation: BMC Medical Informatics and Decision Making 2023 23:201
  26. Healthcare is increasingly digitized, yet remote and automated machine learning (ML) triage prediction systems for virtual urgent care use remain limited. The Canadian Triage and Acuity Scale (CTAS) is the gol...

    Authors: Justin N. Hall, Ron Galaev, Marina Gavrilov and Shawn Mondoux
    Citation: BMC Medical Informatics and Decision Making 2023 23:200
  27. Depression and anxiety can cause social, behavioral, occupational, and functional impairments if not controlled and managed. Mobile-based self-care applications can play an essential and effective role in cont...

    Authors: Khadijeh Moulaei, Kambiz Bahaadinbeigy, Esmat Mashoof and Fatemeh Dinari
    Citation: BMC Medical Informatics and Decision Making 2023 23:199
  28. Even for an experienced neurophysiologist, it is challenging to look at a single graph of an unlabeled motor evoked potential (MEP) and identify the corresponding muscle. We demonstrate that supervised machine...

    Authors: Jonathan Wermelinger, Qendresa Parduzi, Murat Sariyar, Andreas Raabe, Ulf C. Schneider and Kathleen Seidel
    Citation: BMC Medical Informatics and Decision Making 2023 23:198
  29. To analyze the tongue feature of NSCLC at different stages, as well as the correlation between tongue feature and tumor marker, and investigate the feasibility of establishing prediction models for NSCLC at di...

    Authors: Yulin Shi, Hao Wang, Xinghua Yao, Jun Li, Jiayi Liu, Yuan Chen, Lingshuang Liu and Jiatuo Xu
    Citation: BMC Medical Informatics and Decision Making 2023 23:197
  30. Fraud, Waste, and Abuse (FWA) in medical claims have a negative impact on the quality and cost of healthcare. A major component of FWA in claims is procedure code overutilization, where one or more prescribed ...

    Authors: Michael Suesserman, Samantha Gorny, Daniel Lasaga, John Helms, Dan Olson, Edward Bowen and Sanmitra Bhattacharya
    Citation: BMC Medical Informatics and Decision Making 2023 23:196
  31. Loss of cognitive and executive functions is a problem that affects people of all ages. That is why it is important to perform exercises for memory training and prevent early cognitive deterioration. The aim o...

    Authors: José Luis Varela-Aldás, Jorge Buele, Doris Pérez and Guillermo Palacios-Navarro
    Citation: BMC Medical Informatics and Decision Making 2023 23:195
  32. Digital technology tailored for those with limited health literacy has the potential to reduce health inequalities. Although mobile apps can support self-management in chronic diseases, there is little evidenc...

    Authors: Hani Salim, Ai Theng Cheong, Sazlina Sharif-Ghazali, Ping Yein Lee, Poh Ying Lim, Ee Ming Khoo, Norita Hussein, Noor Harzana Harrun, Bee Kiau Ho and Hilary Pinnock
    Citation: BMC Medical Informatics and Decision Making 2023 23:194
  33. An unprecedented acceleration in digital mental health services happened during the COVID-19 pandemic. However, people with severe mental ill health (SMI) might be at risk of digital exclusion, partly because ...

    Authors: P Spanakis, B Lorimer, E Newbronner, R Wadman, S Crosland, S Gilbody, G Johnston, L. Walker and E Peckham
    Citation: BMC Medical Informatics and Decision Making 2023 23:193
  34. Accurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation helps clinicians to better diagnose and evaluation of any treatment r...

    Authors: Yousef Gheibi, Kimia Shirini, Seyed Naser Razavi, Mehdi Farhoudi and Taha Samad-Soltani
    Citation: BMC Medical Informatics and Decision Making 2023 23:192
  35. For optimal health, the maternal, newborn, and child healthcare (MNCH) continuum necessitates that the mother/child receive the full package of antenatal, intrapartum, and postnatal care. In sub-Saharan Africa...

    Authors: Chenai Mlandu, Zvifadzo Matsena-Zingoni and Eustasius Musenge
    Citation: BMC Medical Informatics and Decision Making 2023 23:191
  36. The exponential growth of digital healthcare data is fueling the development of Knowledge Discovery in Databases (KDD). Extracting temporal relationships between medical events is essential to reveal hidden pa...

    Authors: Alicia Ageno, Neus Català and Marcel Pons
    Citation: BMC Medical Informatics and Decision Making 2023 23:189
  37. Data mining of electronic health records (EHRs) has a huge potential for improving clinical decision support and to help healthcare deliver precision medicine. Unfortunately, the rule-based and machine learnin...

    Authors: Geir Thore Berge, Ole-Christoffer Granmo, Tor Oddbjørn Tveit, Anna Linda Ruthjersen and Jivitesh Sharma
    Citation: BMC Medical Informatics and Decision Making 2023 23:188
  38. Mobile health is gradually revolutionizing the way medical care is delivered worldwide. In Mozambique, a country with a high human immunodeficiency virus prevalence, where antiretroviral treatment coverage is ...

    Authors: E. Karajeanes, D. Bila, M. Luis, M. Tovela, C. Anjos, N. Ramanlal, P. Vaz and L. V. Lapão
    Citation: BMC Medical Informatics and Decision Making 2023 23:187
  39. With the global spread of COVID-19, detecting high-risk countries/regions timely and dynamically is essential; therefore, we sought to develop automatic, quantitative and scalable analysis methods to observe a...

    Authors: Xiang Zhou, Xudong Ma, Sifa Gao, Yingying Ma, Jianwei Gao, Huizhen Jiang, Weiguo Zhu, Na Hong, Yun Long and Longxiang Su
    Citation: BMC Medical Informatics and Decision Making 2023 21(Suppl 9):384

    This article is part of a Supplement: Volume 21 Supplement 9

  40. This study aimed to construct a mortality model for the risk stratification of intensive care unit (ICU) patients with sepsis by applying a machine learning algorithm.

    Authors: Jinhu Zhuang, Haofan Huang, Song Jiang, Jianwen Liang, Yong Liu and Xiaxia Yu
    Citation: BMC Medical Informatics and Decision Making 2023 23:185
  41. Aggregate electronic data repositories and population-level cross-sectional surveys play a critical role in HIV programme monitoring and surveillance for data-driven decision-making. However, these data source...

    Authors: Margaret Ndisha, Amin S. Hassan, Faith Ngari, Evans Munene, Mary Gikura, Koske Kimutai, Kennedy Muthoka, Lisa Amai Murie, Herman Tolentino, Jacob Odhiambo, Pascal Mwele, Lydia Odero, Kate Mbaire, Gonza Omoro and Davies O. Kimanga
    Citation: BMC Medical Informatics and Decision Making 2023 23:183
  42. This prospective study aimed to compare telemedicine-assisted structured self-monitoring of blood glucose(SMBG) with a traditional blood glucose meter (BGM) in adults of type 2 diabetes mellitus (T2DM).

    Authors: Chen-Yu Han, Jian Zhang, Xiao-Mei Ye, Jia-Ping Lu, Hai-Ying Jin, Wei-Wei Xu, Ping Wang and Min Zhang
    Citation: BMC Medical Informatics and Decision Making 2023 23:182
  43. Cirrhosis is associated with sarcopaenia and fat wasting, which drive decompensation and mortality. Currently, nutritional status, through body composition assessment, is not routinely monitored in outpatients...

    Authors: K. Gananandan, V. Thomas, W. L. Woo, R. Boddu, R. Kumar, M. Raja, A. Balaji, K. Kazankov and R. P. Mookerjee
    Citation: BMC Medical Informatics and Decision Making 2023 23:180

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