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Clinical decision-making, knowledge support systems, and theory

Section edited by Paul Taylor

This section aims to publish studies on the development, implementation and evaluation of clinical decision support systems. The section also accepts articles on the theoretical support of clinical decision-making (including shared-decision making), decision analysis, and decision aids.

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  1. Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied ...

    Authors: Carole H. Sudre, Jasmina Panovska-Griffiths, Eser Sanverdi, Sebastian Brandner, Vasileios K. Katsaros, George Stranjalis, Francesca B. Pizzini, Claudio Ghimenton, Katarina Surlan-Popovic, Jernej Avsenik, Maria Vittoria Spampinato, Mario Nigro, Arindam R. Chatterjee, Arnaud Attye, Sylvie Grand, Alexandre Krainik…

    Citation: BMC Medical Informatics and Decision Making 2020 20:149

    Content type: Research article

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  2. Prostate cancer (PCa) represents a significant healthcare problem. The critical clinical question is the need for a biopsy. Accurate risk stratification of patients before a biopsy can allow for individualised...

    Authors: Amirhossein Jalali, Robert W. Foley, Robert M. Maweni, Keefe Murphy, Dara J. Lundon, Thomas Lynch, Richard Power, Frank O’Brien, Kieran J. O’Malley, David J. Galvin, Garrett C. Durkan, T. Brendan Murphy and R. William Watson

    Citation: BMC Medical Informatics and Decision Making 2020 20:148

    Content type: Research article

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  3. The design and internal layout of modern operating rooms (OR) are influencing the surgical team’s collaboration and communication, ergonomics, as well as intraoperative hygiene substantially. Yet, there is no ...

    Authors: Juliane Neumann, Christine Angrick, Celina Höhn, Dirk Zajonz, Mohamed Ghanem, Andreas Roth and Thomas Neumuth

    Citation: BMC Medical Informatics and Decision Making 2020 20:145

    Content type: Research article

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  4. Clinical intuition and nonanalytic reasoning play a major role in clinical hypothesis generation; however, clinicians’ intuition about whether a critically ill child is bacteremic has not been explored. We end...

    Authors: Katherine E. M. Hoops, James C. Fackler, Anne King, Elizabeth Colantuoni, Aaron M. Milstone and Charlotte Woods-Hill

    Citation: BMC Medical Informatics and Decision Making 2020 20:144

    Content type: Research article

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  5. The main objective of phase I cancer clinical trials is to identify the maximum tolerated dose, usually defined as the highest dose associated with an acceptable level of severe toxicity during the first cycle...

    Authors: D. Dinart, J. Fraisse, D. Tosi, A. Mauguen, C. Touraine, S. Gourgou, M. C. Le Deley, C. Bellera and C. Mollevi

    Citation: BMC Medical Informatics and Decision Making 2020 20:134

    Content type: Software

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  6. Cancer is a leading cause of death in the United States. Primary care providers (PCPs) juggle patient cancer prevention and screening along with managing acute and chronic health problems. However, clinical de...

    Authors: Melissa L. Harry, Daniel M. Saman, Anjali R. Truitt, Clayton I. Allen, Kayla M. Walton, Patrick J. O’Connor, Heidi L. Ekstrom, JoAnn M. Sperl-Hillen, Joseph A. Bianco and Thomas E. Elliott

    Citation: BMC Medical Informatics and Decision Making 2020 20:117

    Content type: Research article

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  7. Learning from routine healthcare data is important for the improvement of the quality of care. Providing feedback on clinicians’ performance in comparison to their peers has been shown to be more efficient for...

    Authors: Kassaye Yitbarek Yigzaw, Andrius Budrionis, Luis Marco-Ruiz, Torje Dahle Henriksen, Peder A. Halvorsen and Johan Gustav Bellika

    Citation: BMC Medical Informatics and Decision Making 2020 20:116

    Content type: Technical advance

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  8. Incorporating patient preference (PP) information into decision-making has become increasingly important to many stakeholders. However, there is little guidance on which patient preference assessment methods, ...

    Authors: Chiara Whichello, Bennett Levitan, Juhaeri Juhaeri, Vaishali Patadia, Rachael DiSantostefano, Cathy Anne Pinto and Esther W. de Bekker-Grob

    Citation: BMC Medical Informatics and Decision Making 2020 20:114

    Content type: Research article

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  9. Early warning scores (EWS) have been developed as clinical prognostication tools to identify acutely deteriorating patients. In the past few years, there has been a proliferation of studies that describe the d...

    Authors: Andrew Hao Sen Fang, Wan Tin Lim and Tharmmambal Balakrishnan

    Citation: BMC Medical Informatics and Decision Making 2020 20:111

    Content type: Research article

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  10. There are increasing examples of linking data on healthcare resource use and patient outcomes from different sectors of health and social care systems. Linked data are generally anonymised, meaning in most jur...

    Authors: Mary P. Tully, Cecilia Bernsten, Mhairi Aitken and Caroline Vass

    Citation: BMC Medical Informatics and Decision Making 2020 20:109

    Content type: Research article

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  11. IT systems in the healthcare field can have a marked sociotechnical impact: they modify communication habits, alter clinical processes and may have serious ethical implications. The introduction of such system...

    Authors: Heiko Waldmüller, Cord Spreckelsen, Hannah Rudat, Norbert Krumm, Roman Rolke and Stephan Michael Jonas

    Citation: BMC Medical Informatics and Decision Making 2020 20:101

    Content type: Research article

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  12. Treatment decision-making by family members on behalf of patients with major stroke can be challenging because of the shock of the diagnosis and lack of knowledge of the patient’s treatment preferences. We aim...

    Authors: A. Visvanathan, G. E. Mead, M. Dennis, W. N. Whiteley, F. N. Doubal and J. Lawton

    Citation: BMC Medical Informatics and Decision Making 2020 20:98

    Content type: Research article

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  13. Constrained budgets within healthcare systems and the need to efficiently allocate resources often necessitate the valuation of healthcare interventions and services. However, when a technological product is d...

    Authors: Emmanouil Mentzakis, Daria Tkacz and Carol Rivas

    Citation: BMC Medical Informatics and Decision Making 2020 20:95

    Content type: Research article

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  14. Medication errors have been identified as the most common preventable cause of adverse events. The lack of granularity in medication error terminology has led pharmacovigilance experts to rely on information i...

    Authors: Nadine Kadi Eskildsen, Robert Eriksson, Sten B. Christensen, Tamilla Stine Aghassipour, Mikael Juul Bygsø, Søren Brunak and Suzanne Lisbet Hansen

    Citation: BMC Medical Informatics and Decision Making 2020 20:94

    Content type: Research article

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  15. Implementation theories, models and frameworks offer guidance when implementing and sustaining healthcare evidence-based interventions. However, selection can be challenging given the myriad of potential optio...

    Authors: Lisa Strifler, Jan M. Barnsley, Michael Hillmer and Sharon E. Straus

    Citation: BMC Medical Informatics and Decision Making 2020 20:91

    Content type: Research article

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  16. Coronary heart disease (CHD) is a leading cause of morbidity and mortality for breast cancer survivors, yet the joint effect of adverse cardiovascular health (CVH) and cardiotoxic cancer treatments on post-tre...

    Authors: Aixia Guo, Kathleen W. Zhang, Kristi Reynolds and Randi E. Foraker

    Citation: BMC Medical Informatics and Decision Making 2020 20:88

    Content type: Research article

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  17. Basal cell carcinoma (BCC) is a slow-growing, rarely lethal skin cancer that affects people 65 years or older. A range of treatment options exist for BCC, but there is little evidence available to guide patien...

    Authors: Alexandra Junn, Neha R Shukla, Lily Morrison, Meghan Halley, Mary-Margaret Chren, Louise C. Walter, Dominick L. Frosch, Dan Matlock, Jeanette S. Torres and Eleni Linos

    Citation: BMC Medical Informatics and Decision Making 2020 20:81

    Content type: Research article

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  18. Avoidable use of diagnostic tests can both harm patients and increase the cost of healthcare. Nudge-type educational interventions have potential to modify clinician behaviour while respecting clinical autonom...

    Authors: Ben Young, Andrew W. Fogarty, Rob Skelly, Dominick Shaw, Nigel Sturrock, Mark Norwood, Peter Thurley, Sarah Lewis, Tessa Langley and Jo Cranwell

    Citation: BMC Medical Informatics and Decision Making 2020 20:80

    Content type: Research article

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  19. Screening with prostate-specific antigen (PSA) test for prostate cancer is considered a preference sensitive decision; meaning it does not only depend on what is best from a medical point of view, but also fro...

    Authors: S. Baptista, B. Heleno, A. Teixeira, K. L. Taylor and C. Martins

    Citation: BMC Medical Informatics and Decision Making 2020 20:78

    Content type: Study protocol

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  20. Improving medication safety is a major concern in primary care settings worldwide. The Salford Medication safety dASHboard (SMASH) intervention provided general practices in Salford (Greater Manchester, UK) wi...

    Authors: Mark Jeffries, Wouter T. Gude, Richard N. Keers, Denham L. Phipps, Richard Williams, Evangelos Kontopantelis, Benjamin Brown, Anthony J. Avery, Niels Peek and Darren M. Ashcroft

    Citation: BMC Medical Informatics and Decision Making 2020 20:69

    Content type: Research article

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  21. Prostate-Specific Antigen (PSA) screening for early detection of prostate cancer (PCa) may prevent some cancer deaths, but also may miss some cancers or lead to unnecessary and potentially harmful treatment. T...

    Authors: Søren Birkeland, Susanne S. Pedersen, Anders K. Haakonsson, Michael J. Barry and Nina Rottmann

    Citation: BMC Medical Informatics and Decision Making 2020 20:65

    Content type: Research article

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  22. Telemedicine and telephone-triage may compromise patient safety, particularly if urgency is underestimated. We aimed to explore the level of safety of a pediatric telemedicine service, with particular referenc...

    Authors: Motti Haimi, Shuli Brammli-Greenberg, Orna Baron-Epel and Yehezkel Waisman

    Citation: BMC Medical Informatics and Decision Making 2020 20:63

    Content type: Research article

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  23. User interface (UI) design features such as screen layout, density of information, and use of colour may affect the usability of electronic prescribing (EP) systems, with usability problems previously associat...

    Authors: Lisa Aufegger, Naresh Serou, Shiping Chen and Bryony Dean Franklin

    Citation: BMC Medical Informatics and Decision Making 2020 20:62

    Content type: Research article

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  24. Although cancer survivorship care plans have been in use for several years, they have been shown to not be effective in meeting the long-term needs of cancer survivors, in addition being generic and passive in...

    Authors: Akshat Kapoor and Priya Nambisan

    Citation: BMC Medical Informatics and Decision Making 2020 20:59

    Content type: Research article

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  25. During the process of decision-making for long-term care, clients are often dependent on informal support and available information about quality ratings of care services. However, clients do not take ratings ...

    Authors: Catharina M. van Leersum, Albine Moser, Ben van Steenkiste, Marion Reinartz, Esther Stoffers, Judith R. L. M. Wolf and Trudy van der Weijden

    Citation: BMC Medical Informatics and Decision Making 2020 20:57

    Content type: Research article

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  26. Primary care electronic medical record (EMR) data are emerging as a useful source for secondary uses, such as disease surveillance, health outcomes research, and practice improvement. These data capture clinic...

    Authors: Stephanie Garies, Michael Cummings, Hude Quan, Kerry McBrien, Neil Drummond, Donna Manca and Tyler Williamson

    Citation: BMC Medical Informatics and Decision Making 2020 20:56

    Content type: Research article

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  27. Many colorectal cancer (CRC) survivors experience persisting health problems post-treatment that compromise their health-related quality of life (HRQoL). Prediction models are useful tools for identifying surv...

    Authors: Dóra Révész, Sander M. J. van Kuijk, Floortje Mols, Fränzel J. B. van Duijnhoven, Renate M. Winkels, Huub Hoofs, I Jmert Kant, Luc J. Smits, Stéphanie O. Breukink, Lonneke V. van de Poll-Franse, Ellen Kampman, Sandra Beijer, Matty P. Weijenberg and Martijn J. L. Bours

    Citation: BMC Medical Informatics and Decision Making 2020 20:54

    Content type: Research article

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  28. Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in...

    Authors: Hao Xu, Steven Cox, Lisa Stillwell, Emily Pfaff, James Champion, Stanley C. Ahalt and Karamarie Fecho

    Citation: BMC Medical Informatics and Decision Making 2020 20:53

    Content type: Software

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  29. A variant of unknown significance (VUS) is a variant form of a gene that has been identified through genetic testing, but whose significance to the organism function is not known. An actual challenge in precis...

    Authors: Priscilla Machado do Nascimento, Inácio Gomes Medeiros, Raul Maia Falcão, Beatriz Stransky and Jorge Estefano Santana de Souza

    Citation: BMC Medical Informatics and Decision Making 2020 20:52

    Content type: Technical advance

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  30. The use of clinical data in electronic health records for machine-learning or data analytics depends on the conversion of free text into machine-readable codes. We have examined the feasibility of capturing th...

    Authors: Daniel B. Hier and Steven U. Brint

    Citation: BMC Medical Informatics and Decision Making 2020 20:47

    Content type: Research article

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  31. Mammographic breast density is an important predictor of breast cancer, but its measurement has limitations related to subjectivity of visual evaluation or to difficult access for automatic volumetric measurem...

    Authors: Adriano L. C. Araújo, Heliana B. Soares, Daniel F. Carvalho, Roberto M. Mendonça and Antonio G. Oliveira

    Citation: BMC Medical Informatics and Decision Making 2020 20:45

    Content type: Technical advance

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  32. In a novel endeavour we aimed to develop a clinically relevant case identification method for use in research about the mental health of children and young people in New Zealand using the Integrated Data Infra...

    Authors: Nicholas Bowden, Sheree Gibb, Hiran Thabrew, Jesse Kokaua, Richard Audas, Sally Merry, Barry Taylor and Sarah E Hetrick

    Citation: BMC Medical Informatics and Decision Making 2020 20:42

    Content type: Research article

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  33. Multiobjective decision-making processes present a high degree of complexity in their solution, and tools such as multicriteria decision analysis appear as a way to facilitate the decision-makers’ solution and...

    Authors: Deyse Gillyane Gomes Camilo, Ricardo Pires de Souza, Talita Dias Chagas Frazão and João Florêncio da Costa Junior

    Citation: BMC Medical Informatics and Decision Making 2020 20:38

    Content type: Research article

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  34. Shared decision making (SDM) contributes to personalized decisions that fit the personal preferences of patients when choosing a treatment for a condition. However, older adults frequently face multiple chroni...

    Authors: Ruth E. Pel-Littel, Julia C. M. van Weert, Mirella M. Minkman, Wilma J. M. Scholte op Reimer, Marjolein H. van de Pol and Bianca M. Buurman

    Citation: BMC Medical Informatics and Decision Making 2020 20:35

    Content type: Research article

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  35. Despite the established evidence and theoretical advances explaining human judgments under uncertainty, developments of mobile health (mHealth) Clinical Decision Support Systems (CDSS) have not explicitly appl...

    Authors: L. Timotijevic, C. E. Hodgkins, A. Banks, P. Rusconi, B. Egan, M. Peacock, E. Seiss, M. M. L. Touray, H. Gage, C. Pellicano, G. Spalletta, F. Assogna, M. Giglio, A. Marcante, G. Gentile, I. Cikajlo…

    Citation: BMC Medical Informatics and Decision Making 2020 20:34

    Content type: Research article

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  36. We developed a system to automatically classify stance towards vaccination in Twitter messages, with a focus on messages with a negative stance. Such a system makes it possible to monitor the ongoing stream of...

    Authors: Florian Kunneman, Mattijs Lambooij, Albert Wong, Antal van den Bosch and Liesbeth Mollema

    Citation: BMC Medical Informatics and Decision Making 2020 20:33

    Content type: Software

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  37. Individualization and patient-specific optimization of treatment is a major goal of modern health care. One way to achieve this goal is the application of high-resolution diagnostics together with the applicat...

    Authors: Katja Hoffmann, Katja Cazemier, Christoph Baldow, Silvio Schuster, Yuri Kheifetz, Sibylle Schirm, Matthias Horn, Thomas Ernst, Constanze Volgmann, Christian Thiede, Andreas Hochhaus, Martin Bornhäuser, Meinolf Suttorp, Markus Scholz, Ingmar Glauche, Markus Loeffler…

    Citation: BMC Medical Informatics and Decision Making 2020 20:28

    Content type: Software

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  38. Maintaining adequate situation awareness is crucial for patient safety. Previous studies found that the use of avatar-based monitoring (Visual Patient Technology) improved the perception of vital signs compare...

    Authors: Olivier Garot, Julian Rössler, Juliane Pfarr, Michael T. Ganter, Donat R. Spahn, Christoph B. Nöthiger and David W. Tscholl

    Citation: BMC Medical Informatics and Decision Making 2020 20:26

    Content type: Research article

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  39. Colon cancer is common worldwide and is the leading cause of cancer-related death. Multiple levels of omics data are available due to the development of sequencing technologies. In this study, we proposed an i...

    Authors: Danyang Tong, Yu Tian, Tianshu Zhou, Qiancheng Ye, Jun Li, Kefeng Ding and Jingsong Li

    Citation: BMC Medical Informatics and Decision Making 2020 20:22

    Content type: Research article

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  40. Antimicrobial prophylaxis is an evidence-proven strategy for reducing procedure-related infections; however, measuring this key quality metric typically requires manual review, due to the way antimicrobial pro...

    Authors: Hillary J. Mull, Kelly Stolzmann, Emily Kalver, Marlena H. Shin, Marin L. Schweizer, Archana Asundi, Payal Mehta, Maggie Stanislawski and Westyn Branch-Elliman

    Citation: BMC Medical Informatics and Decision Making 2020 20:15

    Content type: Research article

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  41. The emergency department is a critical juncture in the trajectory of care of patients with serious, life-limiting illness. Implementation of a clinical decision support (CDS) tool automates identification of o...

    Authors: Audrey Tan, Mark Durbin, Frank R. Chung, Ada L. Rubin, Allison M. Cuthel, Jordan A. McQuilkin, Aram S. Modrek, Catherine Jamin, Nicholas Gavin, Devin Mann, Jordan L. Swartz, Jonathan S. Austrian, Paul A. Testa, Jacob D. Hill and Corita R. Grudzen

    Citation: BMC Medical Informatics and Decision Making 2020 20:13

    Content type: Research article

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  42. In classification and diagnostic testing, the receiver-operator characteristic (ROC) plot and the area under the ROC curve (AUC) describe how an adjustable threshold causes changes in two types of error: false...

    Authors: André M. Carrington, Paul W. Fieguth, Hammad Qazi, Andreas Holzinger, Helen H. Chen, Franz Mayr and Douglas G. Manuel

    Citation: BMC Medical Informatics and Decision Making 2020 20:4

    Content type: Research article

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  43. We used the Surveillance, Epidemiology, and End Results (SEER) database to develop and validate deep survival neural network machine learning (ML) algorithms to predict survival following a spino-pelvic chondr...

    Authors: Sung Mo Ryu, Sung Wook Seo and Sun-Ho Lee

    Citation: BMC Medical Informatics and Decision Making 2020 20:3

    Content type: Research article

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  44. Although Internet-based interventions (IBIs) have been around for two decades, uptake has been slow. Increasing the acceptability of IBIs among end users may increase uptake. In this study, we explored the fac...

    Authors: Sherald Sanchez, Farah Jindani, Jing Shi, Mark van der Maas, Sylvia Hagopian, Robert Murray and Nigel Turner

    Citation: BMC Medical Informatics and Decision Making 2019 19:290

    Content type: Research article

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  45. There are often multiple lesions in breast magnetic resonance imaging (MRI) reports and radiologists usually focus on describing the index lesion that is most crucial to clinicians in determining the managemen...

    Authors: Yi Liu, Qing Liu, Chao Han, Xiaodong Zhang and Xiaoying Wang

    Citation: BMC Medical Informatics and Decision Making 2019 19:288

    Content type: Research article

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  46. Community-acquired pneumonia (CAP) is one of the leading causes of morbidity and mortality in the USA. Our objective was to assess the predictive value on critical illness and disposition of a sequential Bayes...

    Authors: Amado Alejandro Baez, Laila Cochon and Jose Maria Nicolas

    Citation: BMC Medical Informatics and Decision Making 2019 19:284

    Content type: Research article

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  47. Botulinum toxin (BT) injection is a new treatment for spasticity with hemiplegia after stroke. How a patient decides to receive BT injections after becoming aware of the treatment remains unclear. In this expl...

    Authors: Sawako Arai, Yuko Fukase, Akira Okii, Yoshimi Suzukamo and Toshimitsu Suga

    Citation: BMC Medical Informatics and Decision Making 2019 19:280

    Content type: Research article

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  48. With the character of high incidence, high prevalence and high mortality, stroke has brought a heavy burden to families and society in China. In 2009, the Ministry of Health of China launched the China nationa...

    Authors: Xuemeng Li, Di Bian, Jinghui Yu, Mei Li and Dongsheng Zhao

    Citation: BMC Medical Informatics and Decision Making 2019 19:261

    Content type: Research article

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  49. Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems an...

    Authors: Elizabeth Ford, Philip Rooney, Seb Oliver, Richard Hoile, Peter Hurley, Sube Banerjee, Harm van Marwijk and Jackie Cassell

    Citation: BMC Medical Informatics and Decision Making 2019 19:248

    Content type: Research article

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  50. Numerous studies have analyzed the effectiveness of electronic reminder interventions to improve different clinical conditions, and most have reported a small to moderate effect. Few studies, however, have ana...

    Authors: Ermengol Coma, Manuel Medina, Leonardo Méndez, Eduardo Hermosilla, Manuel Iglesias, Carmen Olmos and Sebastian Calero

    Citation: BMC Medical Informatics and Decision Making 2019 19:245

    Content type: Research article

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