Machine learning based endothelial cell image analysis of patients undergoing descemet membrane endothelial keratoplasty surgery
CONCLUSIONS: A model focused on segmenting endothelial cells can be employed to assess the health of the endothelium in DMEK patients.PMID:38491745 | DOI:10.1515/bmt-2023-0126 (Source: Biomedizinische Technik/Biomedical Engineering)
Source: Biomedizinische Technik/Biomedical Engineering - March 16, 2024 Category: Biomedical Engineering Authors: Emine Esra Karaca Feyza Dicle I şık Reza Hassanpour Kas ım Oztoprak Özlem Evren Kemer Source Type: research

Medical textile implants: hybrid fibrous constructions towards improved performances
CONCLUSIONS: The results show that the non-woven layer helps limiting cell proliferation in the plain weave construction and promotes conversely proliferation in the satin construction.PMID:38462974 | DOI:10.1515/bmt-2023-0335 (Source: Biomedizinische Technik/Biomedical Engineering)
Source: Biomedizinische Technik/Biomedical Engineering - March 11, 2024 Category: Biomedical Engineering Authors: Mal èke Zidi Foued Khoffi Elise Girault Antoinette Eidenschenk Romain Barbet Abdel Tazibt Fr éderic Heim Slah Msahli Source Type: research

Hand gesture recognition with deep residual network using Semg signal
CONCLUSIONS: The hand gesture recognition using the proposed model is accurate and improves the effectiveness of the recognition.PMID:38456275 | DOI:10.1515/bmt-2023-0208 (Source: Biomedizinische Technik/Biomedical Engineering)
Source: Biomedizinische Technik/Biomedical Engineering - March 8, 2024 Category: Biomedical Engineering Authors: Abid Saeed Khattak Azlan Bin Mohd Zain Rohayanti Binti Hassan Fakhra Nazar Muhammad Haris Bilal Ashfaq Ahmed Source Type: research

Structural EEG signal analysis for sleep apnea classification
CONCLUSIONS: It was concluded that not only applying different PSD methods, but also EEG signals from different brain regions provided different statistical results in terms of apnea transition states as obtained from KNN classification.PMID:38452359 | DOI:10.1515/bmt-2024-0060 (Source: Biomedizinische Technik/Biomedical Engineering)
Source: Biomedizinische Technik/Biomedical Engineering - March 7, 2024 Category: Biomedical Engineering Authors: Onur Kocak Cansel Ficici Hikmet Firat Ziya Telatar Source Type: research

A new approach for heart disease detection using Motif transform-based CWT's time-frequency images with DenseNet deep transfer learning methods
CONCLUSIONS: The combined approach of MT + CWT + DenseNET yielded an impressive success rate of 99.31 %.PMID:38425179 | DOI:10.1515/bmt-2023-0580 (Source: Biomedizinische Technik/Biomedical Engineering)
Source: Biomedizinische Technik/Biomedical Engineering - March 1, 2024 Category: Biomedical Engineering Authors: Hazret Tekin Y ılmaz Kaya Source Type: research