Journal of evaluation in clinical practice
-
This research aims to develop an effective algorithm for diagnosing COVID-19 in chest X-rays using the transfer learning method and support vector machines. ⋯ This study confirms the importance of applying machine learning methods in medical applications and opens new perspectives for early diagnosis of infectious diseases. The practical application of the obtained results can enhance the efficiency of diagnosis and control the spread of COVID-19, as well as contribute to the development of innovative methods in medical practice.
-
The proposed umbrella review aims to assess the use and impact of clinical pathways on professional practice, patient outcomes, length of hospital stay, hospital costs, patient satisfaction, and hospital staff satisfaction through a synthesis of existing systematic reviews and meta-analyses. ⋯ No patient or public contribution, as this paper is a protocol of an umbrella review.
-
The COVID-19 pandemic necessitated rapid adaptation of clinical competence assessments, including the transition of Objective Structured Clinical Examinations (OSCE) from in-person to virtual formats. This study investigates the construct equivalence of a high-stakes OSCE, originally designed for in-person delivery, when adapted for a virtual format. ⋯ The study found that while examinee ability and case difficulty estimates exhibited some invariance between in-person and virtual OSCE formats, criteria involving physical assessments faced challenges in maintaining construct equivalence. These findings highlight the need for careful consideration in adapting high-stakes clinical assessments to virtual formats to ensure fairness and reliability.
-
The coherence theory of truth, the epistemology of evidence-based medicine, mathematical statistics, and axiomatic mathematics. ⋯ Researchers in EBM should be aware of systemic misconceptions in RCT standards. Pre-measurement can reduce shortcomings, e.g. through calculation how sample differences impact on usual RCT processing, or randomisation is given up in favour of mathematical minimisation of sample differences, i.e. optimising statistical sample equality. Moreover, the promising future of dynamic simulation models is highlighted.
-
Osteoarthritis (OA) is a common degenerative disease of the joints. Risk factors for OA include non-modifiable factors such as age and sex, as well as modifiable factors like physical activity. ⋯ The performance of the model for predicting OA was relatively good. If this model is continuously used and updated, it could be used to predict OA diagnosis, and the predictive performance of the OA model may be further improved.