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AI-supported reasoning in physiotherapy

Mikołajewski Dariusz, Mikołajewska Emilia

Studia i Materiały Informatyki Stosowanej

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2024

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T. 16, nr 2

21--27

EN

Artificial intelligence (AI)-based clinical reasoning support systems in physiotherapy, and in particular data-driven (machine learning) systems, can be useful in making and reviewing decisions regarding functional diagnosis and formulating/maintaining/modifying a rehabilitation programme. The aim of this article is to explore the extent to which the opportunities offered by AI-based systems for clinical reasoning in physiotherapy have been exploited and where the potential for their further stimulated development lies.

PL

Systemy wspomagania wnioskowania klinicznego w fizjoterapii oparte na sztucznej inteligencji, a w szczególności na danych (uczenie maszynowe), mogą być przydatne w podejmowaniu i weryfikacji decyzji dotyczących diagnostyki funkcjonalnej ora formułowania/utrzymywania/modyfikowania programu rehabilitacji. Celem niniejszego artykułu jest zbadanie, w jakim stopniu możliwości oferowane przez systemy oparte na sztucznej inteligencji w zakresie rozumowania klinicznego w fizjoterapii zostały wykorzystane i gdzie leży potencjał ich dalszego stymulowanego rozwoju.

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Evaluation of three educational use cases for using Virtual Patients in Massive Open Online Courses (MOOCs): a Delphi study

Stathakarou N., Zary N., Kononowicz A. A.

Bio-Algorithms and Med-Systems

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2015

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Vol. 11, no. 2

113--119

EN

Massive Open Online Courses (MOOCs) extended with Virtual Patients (VPs) may foster specific medical skills. In particular, three educational use cases have been proposed to enable interactivity and foster clinical reasoning skills training: collective evaluation of decision making in the context of uncertainty, collective repurposing of cases with division of discussion into subgroups, and computational models in short cases for flexible selection and adaptive learning with VPs. The aim of this study was to evaluate the educational strengths and weaknesses of the proposed use cases. Methods: We went through a two-round modified Delphi process. A panel of experts was formed and asked with open-ended questions to identify the strengths and weaknesses of each use case. The obtained responses were categorized thematically; four specific aspects of the use cases were isolated. In the second phase, the panel was asked to read the collected, categorized responses and prioritize the use cases focusing on each of the four identified aspects. Results: Six experts participated in the process. According to their opinion, decision making in uncertain context was the most feasible in implementation and in fostering clinical reasoning skills training; cultural repurposing was judged to leverage the MOOC potential the most; and computational models in short cases were considered the most interesting use case for the learners. Conclusions: The use cases were validated and prioritized; the Delphi approach brought insights into the use cases’ potential benefits, threats, and challenges.

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Repurposing virtual patients for clinical reasoning: development of a guideline and assessment of time and effort

Hanebeck B., Tönshoff B., Huwendiek S.

Bio-Algorithms and Med-Systems

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2009

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Vol. 5, no. 9

69--72

EN

Introduction: Fostering clinical reasoning is considered to be one of the major learning goals in medical education. However, there is only limited access to real patients to learn clinical reasoning. This deficiency can be overcome by providing virtual patients as an adjunct to real patient encounters. Research has been carried out on design features for virtual patients, especially to improve clinical diagnostic reasoning skills. However, developing new virtual patient cases from scratch is costly, making it reasonable to repurpose existing cases. Efforts to apply these to already existing virtual patients are, as yet, unreported, but are considered to be considerably lower than creation of new cases. Methods: We established a guideline for repurposing virtual patients for fostering clinical reasoning, which was developed from the literature and from our own experiences in repurposing 15 virtual patients. Furthermore, we documented the associated effort in terms of work hours. Results: The established guideline for repurposing virtual patients for clinical reasoning includes the following six major steps: (1) Case selection and initial check; (2) Literature review; (3) Development of a repurposing concept; (4) Enrichment for fostering clinical reasoning; (5) Reduction of cognitive load; (6) Final checks including review by expert and completion. The six steps are described in detail. The associated time and effort were calculated on average by 33 hours per case. Conclusion: We describe a guideline for repurposing virtual patients for clinical reasoning and its associated time and effort. We hope that others planning to repurpose virtual patients for clinical reasoning find this guideline helpful.

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Integration of virtual patients into existing curricula of bh pediatric departments results of two evaluation studies

Bokonjic D., Petrov B., Masic S., Huwendiek S., Lozo S.

Bio-Algorithms and Med-Systems

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2009

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Vol. 5, no. 9

17--21

EN

Introduction: Virtual patients (VPs) are interactive computer programmes that simulate real-life clinical scenarios. We have identified pediatric departments at BH Medical faculties Foca and Mostar as suitable for introducing virtual patients due to the lack of training in patient management and clinical reasoning. Methodology: We have introduced three virtual patients of the CAMPUS system (www.campusvirtualpatients.com). Our tutors were trained by the staff of the Medical Faculty of Heidelberg University. We organized introduction sessions and then divided our students into small groups. Two studies were done using questionnaires, which measured students' satisfaction, learning outcomes, design of virtual patients and the perception of different integration scenarios. Results: In the study, students estimated virtual patients as a good tool for studying and fostering clinical reasoning. Average mark of each part of the programme measured by questionnaire and total mark of the whole programme was almost the same (Kruskal-Wallis=7,892; P=0,096). Students assessed the virtual patients as very stimulating for learning of pediatrics and emphasized that the experience they gained will help them in the continuation of their education. Students estimated the design and integration of virtual patients into the curriculum as fostering learning. Conclusion: We evaluated the use of VPs at two BH faculties. Results indicate that VPs were well integrated and will help our students to improve their clinical reasoning.