23 July 2024
Electronics | Highly Cited Papers in 2023 in the Section “Bioelectronics”


The “Bioelectronics” Section of the journal Electronics (ISSN: 2079-9292) mainly covers topics that seek to exploit electronics knowledge and execution in the field of biology and medicine for health wellness with research efforts that cross disciplines such as chemistry, life science, physics, electrical engineering, and materials science. Bioelectronic research works in a wide context, encompassing, for example, biosensors, bionics and biomaterials, DNA chips, lab-on-a-chip, innovative devices or advanced signal processes for the prevention, diagnosis, and treatment of physical and mental diseases, robotic devices for patient rehabilitation, bioelectromagnetics, artificial intelligence for improving health, conductive polymers, organic semiconductors, carbon nanotubes, graphene, wearable electronics, and implantable electronics, just to cite a few.

As all of the articles published in our journal are in an open access format, you have free and unlimited access to the full texts. We welcome you to read our most highly cited papers published in 2022 listed below:

1. “Deep Learning and Cloud-Based Computation for Cervical Spine Fracture Detection System”
by Paweł Chłąd and Marek R. Ogiela
Electronics 2023, 12(9), 2056; https://doi.org/10.3390/electronics12092056
Available online: https://www.mdpi.com/2079-9292/12/9/2056

2. “Lightweight Deep Learning Model for Real-Time Colorectal Polyp Segmentation”
by Seung-Min Jeong, Seung-Gun Lee, Chae-Lin Seok, Eui-Chul Lee and Jun-Young Lee
Electronics 2023, 12(9), 1962; https://doi.org/10.3390/electronics12091962
Available online: https://www.mdpi.com/2079-9292/12/9/1962

3. “IoT System for Gluten Prediction in Flour Samples Using NIRS Technology, Deep and Machine Learning Techniques”
by Oscar Jossa-Bastidas, Ainhoa Osa Sanchez, Leire Bravo-Lamas and Begonya Garcia-Zapirain
Electronics 2023, 12(8), 1916; https://doi.org/10.3390/electronics12081916
Available online: https://www.mdpi.com/2079-9292/12/8/1916

4. “Reviewing Multimodal Machine Learning and Its Use in Cardiovascular Diseases Detection”
by Mohammad Moshawrab, Mehdi Adda, Abdenour Bouzouane, Hussein Ibrahim and Ali Raad
Electronics 2023, 12(7), 1558; https://doi.org/10.3390/electronics12071558
Available online: https://www.mdpi.com/2079-9292/12/7/1558

5. “EMG-Based Dynamic Hand Gesture Recognition Using Edge AI for Human–Robot Interaction”
by EunSu Kim, JaeWook Shin, YongSung Kwon and BumYong Park
Electronics 2023, 12(7), 1541; https://doi.org/10.3390/electronics12071541
Available online: https://www.mdpi.com/2079-9292/12/7/1541

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