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  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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

  12. 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
  13. 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
  14. 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
  15. Prognostic models of hospital-induced delirium, that include potential predisposing and precipitating factors, may be used to identify vulnerable patients and inform the implementation of tailored preventive i...

    Authors: Urszula A. Snigurska, Sarah E. Ser, Laurence M. Solberg, Mattia Prosperi, Tanja Magoc, Zhaoyi Chen, Jiang Bian, Ragnhildur I. Bjarnadottir and Robert J. Lucero
    Citation: BMC Medical Informatics and Decision Making 2023 23:181
  16. 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
  17. Addressing the current complexities, costs, and adherence issues in the detection of forward head posture (FHP), our study conducted an exhaustive epidemiologic investigation, incorporating a comprehensive pos...

    Authors: Guang Yang, Shichun He, Deyu Meng, Meiqi Wei, Jianwei Cao, Hongzhi Guo, He Ren and Ziheng Wang
    Citation: BMC Medical Informatics and Decision Making 2023 23:179
  18. Food frequency questionnaires (FFQs) are one of the most useful tools for studying and understanding diet-disease relationships. However, because FFQs are self-reported data, they are susceptible to response b...

    Authors: Anjolaoluwa Ayomide Popoola, Jennifer Koren Frediani, Terryl Johnson Hartman and Kamran Paynabar
    Citation: BMC Medical Informatics and Decision Making 2023 23:178
  19. Mobile apps facilitate patients’ access to portals and interaction with their healthcare providers. The COVID-19 pandemic accelerated this trend globally, but little evidence exists on patient portal usage in ...

    Authors: Noha El Yaman, Jad Zeitoun, Rawan Diab, Mohamad Mdaihly, Razan Diab, Lynn Kobeissi, Salwa Abou Ljoud, Jumana Antoun and Marco Bardus
    Citation: BMC Medical Informatics and Decision Making 2023 23:177
  20. Health information technologies play a vital role in addressing diverse health needs among women, offering a wide array of services tailored to their specific requirements. Despite the potential benefits, the ...

    Authors: Khadijeh Moulaei, Reza Moulaei and Kambiz Bahaadinbeigy
    Citation: BMC Medical Informatics and Decision Making 2023 23:176
  21. Malignant hyperthermia (MH) is a rare anesthetic emergency with a high mortality rate in China. We developed a WeChat applet–based National Remote Emergency System for Malignant Hyperthermia (MH-NRES) to provi...

    Authors: Hong Yu, Lingcan Tan, Tao Zhu and Xiaoqian Deng
    Citation: BMC Medical Informatics and Decision Making 2023 23:175
  22. This retrospective study aims to validate the effectiveness of artificial intelligence (AI) to detect and classify non-mass breast lesions (NMLs) on ultrasound (US) images.

    Authors: Guoqiu Li, Hongtian Tian, Huaiyu Wu, Zhibin Huang, Keen Yang, Jian Li, Yuwei Luo, Siyuan Shi, Chen Cui, Jinfeng Xu and Fajin Dong
    Citation: BMC Medical Informatics and Decision Making 2023 23:174
  23. Chronic kidney disease (CKD) is a global public health concern. Therefore, to provide timely intervention for non-hospitalized high-risk patients and rationally allocate limited clinical resources is important...

    Authors: Yufei Lu, Yichun Ning, Yang Li, Bowen Zhu, Jian Zhang, Yan Yang, Weize Chen, Zhixin Yan, Annan Chen, Bo Shen, Yi Fang, Dong Wang, Nana Song and Xiaoqiang Ding
    Citation: BMC Medical Informatics and Decision Making 2023 23:173
  24. Evidence-based medicine (EBM) bridges research and clinical practice to enhance medical knowledge and improve patient care. However, clinical decisions in many African countries don’t base on the best availabl...

    Authors: Habtamu Setegn Ngusie, Mohammadjud Hasen Ahmed, Shegaw Anagaw Mengiste, Mihretu M. Kebede, Shuayib Shemsu, Shuma Gosha Kanfie, Sisay Yitayih Kassie, Mulugeta Hayelom Kalayou and Monika Knudsen Gullslett
    Citation: BMC Medical Informatics and Decision Making 2023 23:172
  25. Anti-thrombotic therapy is the basis of thrombosis prevention and treatment. Bleeding is the main adverse event of anti-thrombosis. Existing laboratory indicators cannot accurately reflect the real-time coagul...

    Authors: Daonan Chen, Rui Wang, Yihan Jiang, Zijian Xing, Qiuyang Sheng, Xiaoqing Liu, Ruilan Wang, Hui Xie and Lina Zhao
    Citation: BMC Medical Informatics and Decision Making 2023 23:171
  26. The risk of mortality in intensive care units (ICUs) is currently addressed by the implementation of scores using admission data. Their performances are satisfactory when complications occur early after admiss...

    Authors: Bertrand Bouvarel, Fabrice Carrat and Nathanael Lapidus
    Citation: BMC Medical Informatics and Decision Making 2023 23:170
  27. The COVID-19 patients in the convalescent stage noticeably have pulmonary diffusing capacity impairment (PDCI). The pulmonary diffusing capacity is a frequently-used indicator of the COVID-19 survivors’ progno...

    Authors: Fu-qiang Ma, Cong He, Hao-ran Yang, Zuo-wei Hu, He-rong Mao, Cun-yu Fan, Yu Qi, Ji-xian Zhang and Bo Xu
    Citation: BMC Medical Informatics and Decision Making 2023 23:169
  28. Early identification of dementia is crucial for prompt intervention for high-risk individuals in the general population. External validation studies on prognostic models for dementia have highlighted the need ...

    Authors: Emma L. Twait, Constanza L. Andaur Navarro, Vilmunur Gudnason, Yi-Han Hu, Lenore J. Launer and Mirjam I. Geerlings
    Citation: BMC Medical Informatics and Decision Making 2023 23:168
  29. Functional gastrointestinal disorders (FGIDs), as a group of syndromes with no identified structural or pathophysiological biomarkers, are currently classified by Rome criteria based on gastrointestinal sympto...

    Authors: Elahe Mousavi, Ammar Hasanzadeh Keshteli, Mohammadreza Sehhati, Ahmad Vaez and Peyman Adibi
    Citation: BMC Medical Informatics and Decision Making 2023 23:167
  30. Large-scale medical equipment, which is extensively implemented in medical services, is of vital importance for diagnosis but vulnerable to various anomalies and failures. Most hospitals that conduct regular m...

    Authors: Changxi Wang, Qilin Liu, Haopeng Zhou, Tong Wu, Haowen Liu, Jin Huang, Yixuan Zhuo, Zhenlin Li and Kang Li
    Citation: BMC Medical Informatics and Decision Making 2023 23:166
  31. Heart failure (HF) is one of the common adverse cardiovascular events after acute myocardial infarction (AMI), but the predictive efficacy of numerous machine learning (ML) built models is unclear. This study ...

    Authors: Xuewen Li, Chengming Shang, Changyan Xu, Yiting Wang, Jiancheng Xu and Qi Zhou
    Citation: BMC Medical Informatics and Decision Making 2023 23:165
  32. Shared decision-making (SDM) is a collaborative process whereby patients and clinicians jointly deliberate on the best treatment option that takes into account patients’ preferences and values. In breast cance...

    Authors: Natalia Oprea, Vittoria Ardito and Oriana Ciani
    Citation: BMC Medical Informatics and Decision Making 2023 23:164
  33. Treatment with oral anticoagulants (OACs) could prevent stroke in atrial fibrillation (AF), but side effects developed due to OACs may cause patients anxiety during decision making. This study aimed to investi...

    Authors: Hsiao-Hui Chiu, Shih-Lin Chang, Hao-Min Cheng, Tze-Fan Chao, Yenn-Jiang Lin, Li-Wei Lo, Yu-Feng Hu, Fa-Po Chung, Jo-Nan Liao, Ta-Chuan Tuan, Chin-Yu Lin, Ting-Yung Chang, Ling Kuo, Chih-Min Liu, Yung-Nan Tsai, Yu-Ting Huang…
    Citation: BMC Medical Informatics and Decision Making 2023 23:163
  34. The utilization of dermoscopic analysis is becoming increasingly critical for diagnosing skin diseases by physicians and even artificial intelligence. With the expansion of dermoscopy, its vocabulary has proli...

    Authors: Xinyuan Zhang, Rebecca Z. Lin, Muhammad “Tuan” Amith, Cynthia Wang, Jeremy Light, John Strickley and Cui Tao
    Citation: BMC Medical Informatics and Decision Making 2023 23(Suppl 1):162

    This article is part of a Supplement: Volume 23 Supplement 1

  35. Previous studies have already shown that decision aids are a suitable tool for patient decision-making. The aim of this work is to conduct an online search for freely available, German-language patient decisio...

    Authors: Julia Möller, Lena Josfeld, Christian Keinki, Nathalie Zieglowski, Jens Büntzel and Jutta Hübner
    Citation: BMC Medical Informatics and Decision Making 2023 23:161
  36. Differentiating between Crohn’s disease (CD) and intestinal tuberculosis (ITB) with endoscopy is challenging. We aim to perform more accurate endoscopic diagnosis between CD and ITB by building a trustworthy A...

    Authors: Keming Lu, Yuanren Tong, Si Yu, Yucong Lin, Yingyun Yang, Hui Xu, Yue Li and Sheng Yu
    Citation: BMC Medical Informatics and Decision Making 2023 23:160
  37. Current healthcare trends emphasize the use of shared decision-making (SDM) for renal replacement treatment (RRT) in patients with chronic kidney disease (CKD). This is crucial to understand the relationship b...

    Authors: Shih-Ming Hsiao, Mei-Chuan Kuo, Pei-Ni Hsiao, Sin-Hua Moi, Yi-Wen Chiu, Shu-Li Wang, Tzu-Hui Chen, Lan-Fang Kung, Shang-Jyh Hwang and Chia-Lun Lee
    Citation: BMC Medical Informatics and Decision Making 2023 23:159
  38. In the era of electronic health records (EHR), the ability to share clinical data is a key facilitator of healthcare delivery. Since the introduction of EHRs, this aspect has been extensively studied from the ...

    Authors: Edmond Li, Olivia Lounsbury, Jonathan Clarke, Hutan Ashrafian, Ara Darzi and Ana Luisa Neves
    Citation: BMC Medical Informatics and Decision Making 2023 23:158
  39. Artificial intelligence (AI) tools are more effective if accepted by clinicians. We developed an AI-based clinical decision support system (CDSS) to facilitate vancomycin dosing. This qualitative study assesse...

    Authors: Xinyan Liu, Erin F. Barreto, Yue Dong, Chang Liu, Xiaolan Gao, Mohammad Samie Tootooni, Xuan Song and Kianoush B. Kashani
    Citation: BMC Medical Informatics and Decision Making 2023 23:157
  40. Prediction tools for various intraoperative bleeding events remain scarce. We aim to develop machine learning-based models and identify the most important predictors by real-world data from electronic medical ...

    Authors: Ying Shi, Guangming Zhang, Chiye Ma, Jiading Xu, Kejia Xu, Wenyi Zhang, Jianren Wu and Liling Xu
    Citation: BMC Medical Informatics and Decision Making 2023 23:156
  41. The purpose of this paper was to systematically evaluate the application value of artificial intelligence in predicting mortality among COVID-19 patients.

    Authors: Yu Xin, Hongxu Li, Yuxin Zhou, Qing Yang, Wenjing Mu, Han Xiao, Zipeng Zhuo, Hongyu Liu, Hongying Wang, Xutong Qu, Changsong Wang, Haitao Liu and Kaijiang Yu
    Citation: BMC Medical Informatics and Decision Making 2023 23:155
  42. Environmental toxins are particularly harmful to pregnant women and their fetuses due to the long-term effects of these toxins on children after birth. Environmental health behaviors can prevent and protect mo...

    Authors: Hyun Kyoung Kim
    Citation: BMC Medical Informatics and Decision Making 2023 23:154
  43. The recent advances in biotechnology and computer science have led to an ever-increasing availability of public biomedical data distributed in large databases worldwide. However, these data collections are far...

    Authors: Francesco Taglino, Fabio Cumbo, Giulia Antognoli, Ivan Arisi, Mara D’Onofrio, Federico Perazzoni, Roger Voyat, Giulia Fiscon, Federica Conte, Marco Canevelli, Giuseppe Bruno, Patrizia Mecocci and Paola Bertolazzi
    Citation: BMC Medical Informatics and Decision Making 2023 23:153
  44. The progressive ageing in developed countries entails an increase in multimorbidity. Population-wide predictive models for adverse health outcomes are crucial to address these growing healthcare needs. The mai...

    Authors: Alexander Olza, Eduardo Millán and María Xosé Rodríguez-Álvarez
    Citation: BMC Medical Informatics and Decision Making 2023 23:152
  45. In the United States, the National Alzheimer’s Coordinating Center (NACC) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) are two major data sharing resources for Alzheimer’s Disease (AD) research. ...

    Authors: Xubing Hao, Xiaojin Li, Guo-Qiang Zhang, Cui Tao, Paul E. Schulz and Licong Cui
    Citation: BMC Medical Informatics and Decision Making 2023 23(Suppl 1):151

    This article is part of a Supplement: Volume 23 Supplement 1

  46. About 2% of the German population are affected by psoriasis. A growing number of cost-intensive systemic treatments are available. Surveys have shown high proportions of patients with moderate to severe psoria...

    Authors: Lisa Graf, Falko Tesch, Felix Gräßer, Lorenz Harst, Doreen Siegels, Jochen Schmitt and Susanne Abraham
    Citation: BMC Medical Informatics and Decision Making 2023 23:150
  47. Prediction calculators can help set outcomes expectations following orthopaedic surgery, however effective implementation strategies for these tools are unknown. This study evaluated provider and patient persp...

    Authors: Trevor A. Lentz, Byron F. Stephens, Amir M. Abtahi, Jacob Schwarz, Andrew J. Schoenfeld, Bethany A. Rhoten, Shannon Block, Alex O’Brien and Kristin R. Archer
    Citation: BMC Medical Informatics and Decision Making 2023 23:149

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