Skip to main content

Articles

Page 1 of 68

  1. Clinical medicine offers a promising arena for applying Machine Learning (ML) models. However, despite numerous studies employing ML in medical data analysis, only a fraction have impacted clinical care. This ...

    Authors: Christel Sirocchi, Alessandro Bogliolo and Sara Montagna
    Citation: BMC Medical Informatics and Decision Making 2024 24(Suppl 4):186
    Content type: Research Published on:

    This article is part of a Supplement: Volume 24 Supplement 4

  2. This paper outlines the design, implementation, and usability study results of the patient empowerment process for chronic disease management, using Patient Reported Outcome Measurements and Shared Decision-Ma...

    Authors: Gokce B. Laleci Erturkmen, Natassia Kamilla Juul, Irati Erreguerena Redondo, Ana Ortega Gil, Dolores Verdoy Berastegui, Esteban de Manuel, Mustafa Yuksel, Bunyamin Sarigul, Gokhan Yilmaz, Sarah N. L. I. M. Choi Keung, Theodoros N. Arvanitis, Thea Damkjaer Syse, Janika Bloemeke-Cammin, Rachelle Kaye and Anne Dichmann Sorknæs
    Citation: BMC Medical Informatics and Decision Making 2024 24:185
    Content type: Research Published on:

  3. An ever-increasing amount of data on a person’s daily functioning is being collected, which holds information to revolutionize person-centered healthcare. However, the full potential of data on daily functioni...

    Authors: Esther R.C. Janssen, Ilona M. Punt, Johan van Soest, Yvonne F. Heerkens, Hillegonda A. Stallinga, Huib ten Napel, Lodewijk W. van Rhijn, Barend Mons, Andre Dekker, Paul C. Willems and Nico L.U. van Meeteren
    Citation: BMC Medical Informatics and Decision Making 2024 24:184
    Content type: Research Published on:

  4. The analysis of extensive electronic health records (EHR) datasets often calls for automated solutions, with machine learning (ML) techniques, including deep learning (DL), taking a lead role. One common task ...

    Authors: Jenny Yang, Hagen Triendl, Andrew A. S. Soltan, Mangal Prakash and David A. Clifton
    Citation: BMC Medical Informatics and Decision Making 2024 24:183
    Content type: Research Published on:

  5. Theories, models and frameworks (TMFs) are useful when implementing, evaluating and sustaining healthcare evidence-based interventions. Yet it can be challenging to identify an appropriate TMF for an implement...

    Authors: Lisa Strifler, Christine Fahim, Michael P. Hillmer, Jan M. Barnsley and Sharon E. Straus
    Citation: BMC Medical Informatics and Decision Making 2024 24:182
    Content type: Research Published on:

  7. Insurance databases contain valuable information related to the use of dental services. This data is instrumental in decision-making processes, enhancing risk assessment, and predicting outcomes. The objective...

    Authors: Zahra Pouraskari, Reza Yazdani, Maryam Khademi and Hossein Hessari
    Citation: BMC Medical Informatics and Decision Making 2024 24:180
    Content type: Research Published on:

  8. With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges. Various studies have emerged utilizing Artificial Intelligence (AI) and Data Science techniques for disease...

    Authors: Manar Abu Talib, Yaman Afadar, Qassim Nasir, Ali Bou Nassif, Haytham Hijazi and Ahmad Hasasneh
    Citation: BMC Medical Informatics and Decision Making 2024 24:179
    Content type: Research Published on:

  9. This study aimed to develop and validate a quantitative index system for evaluating the data quality of Electronic Medical Records (EMR) in disease risk prediction using Machine Learning (ML).

    Authors: Jiayin Zhou, Jie Hao, Mingkun Tang, Haixia Sun, Jiayang Wang, Jiao Li and Qing Qian
    Citation: BMC Medical Informatics and Decision Making 2024 24:178
    Content type: Research Published on:

  10. Enhancing Local Control (LC) of brain metastases is pivotal for improving overall survival, which makes the prediction of local treatment failure a crucial aspect of treatment planning. Understanding the facto...

    Authors: Hemalatha Kanakarajan, Wouter De Baene, Karin Gehring, Daniëlle B. P. Eekers, Patrick Hanssens and Margriet Sitskoorn
    Citation: BMC Medical Informatics and Decision Making 2024 24:177
    Content type: Systematic Review Published on:

  11. Patient-reported outcome (PRO) is a distinct and indispensable dimension of clinical characteristics and recent advances have made remote PRO measurement possible. Sex difference in PRO of Parkinson’s disease ...

    Authors: Zhiheng Xu, Lirong Jin, Weijie Chen, Tianyu Hu, Shiyu Li, Xiaoniu Liang, Xixi Han, Yi Chen, Yilin Tang, Jian Wang and Danhong Wu
    Citation: BMC Medical Informatics and Decision Making 2024 24:176
    Content type: Research Published on:

  12. Machine Learning (ML) plays a crucial role in biomedical research. Nevertheless, it still has limitations in data integration and irreproducibility. To address these challenges, robust methods are needed. Panc...

    Authors: Tanakamol Mahawan, Teifion Luckett, Ainhoa Mielgo Iza, Natapol Pornputtapong and Eva Caamaño Gutiérrez
    Citation: BMC Medical Informatics and Decision Making 2024 24(Suppl 4):175
    Content type: Research Published on:

    This article is part of a Supplement: Volume 24 Supplement 4

  13. The correlation between radiation exposure before pregnancy and abnormal birth weight has been previously proven. However, for large-for-gestational-age (LGA) babies in women exposed to radiation before becomi...

    Authors: Xi Bai, Zhibo Zhou, Zeyan Zheng, Yansheng Li, Kejia Liu, Yuanjun Zheng, Hongbo Yang, Huijuan Zhu, Shi Chen and Hui Pan
    Citation: BMC Medical Informatics and Decision Making 2024 24:174
    Content type: Research Published on:

  14. Because spontaneous remission is common in IMN, and there are adverse effects of immunosuppressive therapy, it is important to assess the risk of progressive loss of renal function before deciding whether and ...

    Authors: Feng Wang, Jiayi Xu, Fumei Wang, Xu Yang, Yang Xia, Hongli Zhou, Na Yi, Congcong Jiao, Xuesong Su, Beiru Zhang, Hua Zhou and Yanqiu Wang
    Citation: BMC Medical Informatics and Decision Making 2024 24:173
    Content type: Research Published on:

  15. Hematoma expansion (HE) is a high risky symptom with high rate of occurrence for patients who have undergone spontaneous intracerebral hemorrhage (ICH) after a major accident or illness. Correct prediction of ...

    Authors: Yan Li, Chaonan Du, Sikai Ge, Ruonan Zhang, Yiming Shao, Keyu Chen, Zhepeng Li and Fei Ma
    Citation: BMC Medical Informatics and Decision Making 2024 24:172
    Content type: Research Published on:

  16. Digital health is being used as an accelerator to improve the traditional healthcare system, aiding countries in achieving their sustainable development goals. Burkina Faso aims to harmonize its digital health...

    Authors: Bry Sylla, Boukary Ouedraogo, Salif Traore, Ousseni Ouedraogo, Léon Gueswendé Blaise Savadogo and Gayo Diallo
    Citation: BMC Medical Informatics and Decision Making 2024 24:171
    Content type: Research Published on:

  17. Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand fo...

    Authors: Benedetta Gottardelli, Roberto Gatta, Leonardo Nucciarelli, Andrada Mihaela Tudor, Erica Tavazzi, Mauro Vallati, Stefania Orini, Nicoletta Di Giorgi and Andrea Damiani
    Citation: BMC Medical Informatics and Decision Making 2024 24:170
    Content type: Software Published on:

  19. Symptom assessment is central to appropriate adenomyosis management. Using a WeChat mini-program-based portal, we aimed to establish a valid symptom assessment scale of adenomyosis (AM-SAS) to precisely and ti...

    Authors: Wei Xu, Xin Zhang, Fan Xu, Yuan Yuan, Ying Tang and Qiuling Shi
    Citation: BMC Medical Informatics and Decision Making 2024 24:168
    Content type: Research Published on:

  20. Consider a setting where multiple parties holding sensitive data aim to collaboratively learn population level statistics, but pooling the sensitive data sets is not possible due to privacy concerns and partie...

    Authors: Lukas Prediger, Joonas Jälkö, Antti Honkela and Samuel Kaski
    Citation: BMC Medical Informatics and Decision Making 2024 24:167
    Content type: Research Published on:

  21. Cesarean section-induced postpartum hemorrhage (PPH) potentially causes anemia and hypovolemic shock in pregnant women. Hence, it is helpful for obstetricians and anesthesiologists to prepare pre-emptive preve...

    Authors: Meng Wang, Gao Yi, Yunjia Zhang, Mei Li and Jin Zhang
    Citation: BMC Medical Informatics and Decision Making 2024 24:166
    Content type: Research Published on:

  22. Pattern mining techniques are helpful tools when extracting new knowledge in real practice, but the overwhelming number of patterns is still a limiting factor in the health-care domain. Current efforts concern...

    Authors: Isidoro J. Casanova, Manuel Campos, Jose M. Juarez, Antonio Gomariz, Bernardo Canovas-Segura, Marta Lorente-Ros and Jose A. Lorente
    Citation: BMC Medical Informatics and Decision Making 2024 24:165
    Content type: Research Published on:

  23. Mobile phones are potential digital technologies for accessing family planning self-care interventions. However, their utilization could be possible if women of reproductive age have positive attitudes towards...

    Authors: Yagos Onen Walter, Pamela Atim, Derrick Amone, Alarakol Simon Peter and Geoffrey Olok Tabo
    Citation: BMC Medical Informatics and Decision Making 2024 24:164
    Content type: Research Published on:

  24. Chronic kidney disease (CKD) is a significant public health concern, and patient self-management is an effective approach to manage the condition. Mobile applications have been used as tools to assist in impro...

    Authors: Yu Shi, Shi Pu, Hongmei Peng, Jing Zhang, Yang Li, Xia Huang, Caiping Song and Yu Luo
    Citation: BMC Medical Informatics and Decision Making 2024 24:163
    Content type: Research Published on:

  25. Many state-of-the-art results in natural language processing (NLP) rely on large pre-trained language models (PLMs). These models consist of large amounts of parameters that are tuned using vast amounts of tra...

    Authors: Thomas Vakili, Aron Henriksson and Hercules Dalianis
    Citation: BMC Medical Informatics and Decision Making 2024 24:162
    Content type: Research Published on:

  26. This study aimed to develop a higher performance nomogram based on explainable machine learning methods, and to predict the risk of death of stroke patients within 30 days based on clinical characteristics on ...

    Authors: Haoran Chen, Fengchun Yang, Yifan Duan, Lin Yang and Jiao Li
    Citation: BMC Medical Informatics and Decision Making 2024 24:161
    Content type: Research Published on:

  27. Liver disease causes two million deaths annually, accounting for 4% of all deaths globally. Prediction or early detection of the disease via machine learning algorithms on large clinical data have become promi...

    Authors: Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik and Zhongming Zhao
    Citation: BMC Medical Informatics and Decision Making 2024 24:160
    Content type: Research Published on:

  28. Compared with the time-consuming and labor-intensive for biological validation in vitro or in vivo, the computational models can provide high-quality and purposeful candidates in an instant. Existing computati...

    Authors: Yi Zhang, ZhenMei Wang, Hanyan Wei and Min Chen
    Citation: BMC Medical Informatics and Decision Making 2024 24:159
    Content type: Research Published on:

  29. Allogeneic Blood transfusion is common in hip surgery but is associated with increased morbidity. Accurate prediction of transfusion risk is necessary for minimizing blood product waste and preoperative decisi...

    Authors: Han Zang, Ai Hu, Xuanqi Xu, He Ren and Li Xu
    Citation: BMC Medical Informatics and Decision Making 2024 24:158
    Content type: Research Published on:

  30. Learning of burn patient assessment is very important, but heart-breaking for nursing students. This study aimed to compare the effects of feedback lecture method with a serious game (BAM Game) on nursing stud...

    Authors: Amirreza Nasirzade, Kolsoum Deldar, Razieh Froutan and Mohammad Taghi Shakeri
    Citation: BMC Medical Informatics and Decision Making 2024 24:157
    Content type: Research Published on:

  31. In the context of healthcare centered on the patient, Patient Decision Aids (PtDAs) acts as an essential instrument, promoting shared decision-making (SDM). Considering the prevalent occurrence of myopia, the ...

    Authors: Hanieh Delshad Aghdam, Fatemeh Zarei and Seyed Farzad Mohammadi
    Citation: BMC Medical Informatics and Decision Making 2024 24:156
    Content type: Research Published on:

  32. Diagnosis can often be recorded in electronic medical records (EMRs) as free-text or using a term with a diagnosis code. Researchers, governments, and agencies, including organisations that deliver incentivise...

    Authors: Rachel Canaway, Christine Chidgey, Christine Mary Hallinan, Daniel Capurro and Douglas IR Boyle
    Citation: BMC Medical Informatics and Decision Making 2024 24:155
    Content type: Research Published on:

  33. Extracting research of domain criteria (RDoC) from high-risk populations like those with post-traumatic stress disorder (PTSD) is crucial for positive mental health improvements and policy enhancements. The in...

    Authors: Oshin Miranda, Sophie Marie Kiehl, Xiguang Qi, M. Daniel Brannock, Thomas Kosten, Neal David Ryan, Levent Kirisci, Yanshan Wang and LiRong Wang
    Citation: BMC Medical Informatics and Decision Making 2024 24:154
    Content type: Research Published on:

  34. The increased application of Internet of Things (IoT) in healthcare, has fueled concerns regarding the security and privacy of patient data. Lightweight Cryptography (LWC) algorithms can be seen as a potential...

    Authors: Tserendorj Chinbat, Samaneh Madanian, David Airehrour and Farkhondeh Hassandoust
    Citation: BMC Medical Informatics and Decision Making 2024 24:153
    Content type: Research Published on:

  35. Machine learning (ML) has emerged as the predominant computational paradigm for analyzing large-scale datasets across diverse domains. The assessment of dataset quality stands as a pivotal precursor to the suc...

    Authors: Meysam Ahangaran, Hanzhi Zhu, Ruihui Li, Lingkai Yin, Joseph Jang, Arnav P. Chaudhry, Lindsay A. Farrer, Rhoda Au and Vijaya B. Kolachalama
    Citation: BMC Medical Informatics and Decision Making 2024 24:152
    Content type: Software Published on:

  36. BERT models have seen widespread use on unstructured text within the clinical domain. However, little to no research has been conducted into classifying unstructured clinical notes on the basis of patient life...

    Authors: Hielke Muizelaar, Marcel Haas, Koert van Dortmont, Peter van der Putten and Marco Spruit
    Citation: BMC Medical Informatics and Decision Making 2024 24:151
    Content type: Research Published on:

  38. Epilepsy, a chronic brain disorder characterized by abnormal brain activity that causes seizures and other symptoms, is typically treated using anti-epileptic drugs (AEDs) as the first-line therapy. However, d...

    Authors: Daeahn Cho, Myeong-Sang Yu, Jeongyoon Shin, Jingyu Lee, Yubin Kim, Hoon-Chul Kang, Se Hee Kim and Dokyun Na
    Citation: BMC Medical Informatics and Decision Making 2024 24(Suppl 2):149
    Content type: Research Published on:

    This article is part of a Supplement: Volume 24 Supplement 2

  39. This study aimed to create a method for promptly predicting acute kidney injury (AKI) in intensive care patients by applying interpretable, explainable artificial intelligence techniques.

    Authors: Xunliang Li, Peng Wang, Yuke Zhu, Wenman Zhao, Haifeng Pan and Deguang Wang
    Citation: BMC Medical Informatics and Decision Making 2024 24:148
    Content type: Research Published on:

  40. Securing adequate data privacy is critical for the productive utilization of data. De-identification, involving masking or replacing specific values in a dataset, could damage the dataset’s utility. However, f...

    Authors: Eunyoung Im, Hyeoneui Kim, Hyungbok Lee, Xiaoqian Jiang and Ju Han Kim
    Citation: BMC Medical Informatics and Decision Making 2024 24:147
    Content type: Research Published on:

  41. Video consultations between hospital-based neurologists and Emergency Medical Services (EMS) have potential to increase precision of decisions regarding stroke patient assessment, management and transport. In ...

    Authors: Stefan Candefjord, Magnus Andersson Hagiwara, Bengt Arne Sjöqvist, Jan-Erik Karlsson, Annika Nordanstig, Lars Rosengren and Hanna Maurin Söderholm
    Citation: BMC Medical Informatics and Decision Making 2024 24:146
    Content type: Research Published on:

  42. Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm...

    Authors: Junhu Tai, Munsoo Han, Bo Yoon Choi, Sung Hoon Kang, Hyeongeun Kim, Jiwon Kwak, Dabin Lee, Tae Hoon Lee, Yongwon Cho and Tae Hoon Kim
    Citation: BMC Medical Informatics and Decision Making 2024 24:145
    Content type: Research Published on:

    The Correction to this article has been published in BMC Medical Informatics and Decision Making 2024 24:150

  43. Diabetes is a chronic condition that can result in many long-term physiological, metabolic, and neurological complications. Therefore, early detection of diabetes would help to determine a proper diagnosis and...

    Authors: Belqes Alsadi, Saleh Musleh, Hamada R. H. Al-Absi, Mahmoud Refaee, Rizwan Qureshi, Nady El Hajj and Tanvir Alam
    Citation: BMC Medical Informatics and Decision Making 2024 24:144
    Content type: Research Published on:

  44. Post-ERCP pancreatitis is one of the most common adverse events in ERCP-related procedures. The purpose of this study is to construct an online model to predict the risk of post-ERCP pancreatitis in non-elderl...

    Authors: Chaoqun Yan, Jinxin Zheng, Haizheng Tang, Changjian Fang, Jiang Zhu, Hu Feng, Hao Huang, Yilin Su, Gang Wang and Cheng Wang
    Citation: BMC Medical Informatics and Decision Making 2024 24:143
    Content type: Research Published on:

  45. Alzheimer’s Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Given that there is currently no cure, it is critical to detect AD in its early stage during the disease pr...

    Authors: Hoon Seo, Lodewijk Brand and Hua Wang
    Citation: BMC Medical Informatics and Decision Making 2024 24(Suppl 1):61
    Content type: Research Published on:

    This article is part of a Supplement: Volume 24 Supplement 1

  46. Lung cancer remains a leading cause of cancer-related mortality globally, with prognosis significantly dependent on early-stage detection. Traditional diagnostic methods, though effective, often face challenge...

    Authors: M. Mohamed Musthafa, I. Manimozhi, T. R. Mahesh and Suresh Guluwadi
    Citation: BMC Medical Informatics and Decision Making 2024 24:142
    Content type: Research Published on:

  47. Acute pulmonary thromboembolism (PTE) is a common cardiovascular disease and recognizing low prognosis risk patients with PTE accurately is significant for clinical treatment. This study evaluated the value of...

    Authors: Jun Zhou, Xin Wang, Yiyao Li, Yuqing Yang and Juhong Shi
    Citation: BMC Medical Informatics and Decision Making 2024 24:141
    Content type: Research Published on:

  48. Improving shared decision-making using a treat-to-target approach, including the use of clinical outcome measures, is important to providing high quality care for rheumatoid arthritis (RA). We developed an Ele...

    Authors: Catherine Nasrallah, Cherish Wilson, Alicia Hamblin, Cammie Young, Lindsay Jacobsohn, Mary C. Nakamura, Andrew Gross, Mehrdad Matloubian, Judith Ashouri, Jinoos Yazdany and Gabriela Schmajuk
    Citation: BMC Medical Informatics and Decision Making 2024 24:140
    Content type: Research Published on:

  49. Few studies have been conducted on the usage of telehealth focusing on consultations between patients’ families and physicians. This study aimed to identify the usage and limitations of online medical consulta...

    Authors: Tetsuro Hayashi and Seiji Bito
    Citation: BMC Medical Informatics and Decision Making 2024 24:139
    Content type: Research Published on:

  50. Modeling causality through graphs, referred to as causal graph learning, offers an appropriate description of the dynamics of causality. The majority of current machine learning models in clinical decision sup...

    Authors: Hang Wu, Wenqi Shi and May D. Wang
    Citation: BMC Medical Informatics and Decision Making 2024 24:137
    Content type: Research Published on:
Submit manuscript

Annual Journal Metrics

  • 2022 Citation Impact
    3.5 - 2-year Impact Factor
    3.9 - 5-year Impact Factor
    1.384 - SNIP (Source Normalized Impact per Paper)
    0.940 - SJR (SCImago Journal Rank)

    2023 Speed
    37 days submission to first editorial decision for all manuscripts (Median)
    213 days submission to accept (Median)

    2023 Usage 
    2,588,758 downloads
    2,443 Altmetric mentions 

Peer-review Terminology

  • The following summary describes the peer review process for this journal:

    Identity transparency: Single anonymized

    Reviewer interacts with: Editor

    Review information published: Review reports. Reviewer Identities reviewer opt in. Author/reviewer communication

    More information is available here

Follow

Sign up for article alerts and news from this journal

BMC Medical Informatics and Decision Making

ISSN: 1472-6947

Contact us