A5000071358- Artificial Intelligence in Healthcare and Education
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Advanced X-ray and CT Imaging
- Mobile Health and mHealth Applications
- Social Media in Health Education
- Clinical Reasoning and Diagnostic Skills
- Ultrasound in Clinical Applications
- Digital Imaging in Medicine
- Telemedicine and Telehealth Implementation
- Cardiac, Anesthesia and Surgical Outcomes
- Context-Aware Activity Recognition Systems
- Machine Learning in Healthcare
Medical University of Silesia
2022-2024
Rapid development of artificial intelligence has aroused curiosity regarding its potential applications in medical field. The purpose this article was to present the performance ChatGPT, a state-of-the-art language model relation pass rate national specialty examination (PES) radiology and imaging diagnostics within Polish education system. Additionally, study aimed identify strengths limitations through detailed analysis issues raised by exam questions.The utilized PES consisting 120...
AMA Bielówka M, Kufel J, Rojek et al. Evaluating ChatGPT-3.5 in allergology: performance the Polish Specialist Examination. Alergologia Polska - Journal of Allergology. 2024;11(1):42-47. doi:10.5114/pja.2024.135380. APA Bielówka, M., Kufel, J., Rojek, Mitręga, A., Kaczyńska, D., & Czogalik, Ł. (2024). Allergology, 11(1), 42-47. https://doi.org/10.5114/pja.2024.135380 Chicago Michał, Jakub Marcin Adam Dominika Łukasz and Michał Janik 2024. "Evaluating Examination". Allergology 11 (1): Harvard...
AMA Rojek M, Kufel J, Bielówka et al. Exploring the performance of ChatGPT-3.5 in addressing dermatological queries: a research investigation into AI capabilities. Dermatology Review/Przegląd Dermatologiczny. 2024;111(1):26-30. doi:10.5114/dr.2024.140796. APA Rojek, M., Kufel, J., Bielówka, Mitręga, A., Kaczyńska, D., & Czogalik, Ł. (2024). Dermatologiczny, 111(1), 26-30. https://doi.org/10.5114/dr.2024.140796 Chicago Marcin, Jakub Michał Adam Dominika Łukasz and Kondoł 2024. "Exploring...
Objectives: The purpose of this study is to evaluate the performance our deep learning algorithm in calculating cardiothoracic ratio (CTR) and thus assessment cardiomegaly or pericardial effusion occurrences on chest radiography (CXR). Methods: From a database 8000 CXRs, 13 folders with comparable number images were created. Then, 1020 chosen randomly, proportion each folder. Afterward, CTR was calculated using RadiAnt Digital Imaging Communications Medicine (DICOM) Viewer software (2023.1)....
Diagnostic imaging has become an integral part of the healthcare system. In recent years, scientists around world have been working on artificial intelligence-based tools that help in achieving better and faster diagnoses. Their accuracy is crucial for successful treatment, especially diagnostics. This study used a deep convolutional neural network to detect four categories objects digital chest X-ray images. The data were obtained from publicly available National Institutes Health (NIH)...
This study evaluates the effectiveness of ChatGPT-3.5 language model in providing correct answers to pathomorphology questions as required by State Speciality Examination (PES). Artificial intelligence (AI) medicine is generating increasing interest, but its potential needs thorough evaluation. A set 119 exam type and subtype were used, which posed model. Performance was analysed with regard success rate different question categories subtypes. achieved a performance 45.38%, significantly...
As the number of smartphones increases, so does medical apps. Medical mobile applications are widely used in many fields by both patients and doctors. However, there still few approved that can be diagnostic-therapeutic process radiological apps affected as well. We conducted our research classifying from Google Play® store into appropriate categories, according to own qualification system developed researchers for purposes this study. In addition, we also evaluated App Store®. The radiology...