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Abstract This paper described a four-band implantable RF rectifier with simplified circuit complexity. Each RF-rectifier cell is sequentially matched to the four operational frequencies to accomplish the proposed design. The proposed RF rectifier can harvest RF signals at 1.830, 2.100, and white space Wi-Fi bands between 2.38 to 2.68 GHz, respectively. At 2.100 GHz, the proposed RF harvester achieved a maximum (radio frequency direct current) RF-to-DC power conversion efficiency (PCE) of 73.00% and an output DC voltage $$V_{DC}$$ V DC of 1.61 V for an RF power of 2 dBm. The outdoor performance of the rectenna shows a $$V_{DC}$$ V DC of 0.440 V and drives a low-power bq25504-674 evaluation module (EVM) at 1.362 V. The dimension of the RF-rectifier on the FR-4 PCB board is 0.27 $$\lambda _{g}$$ λ g $$\times$$ × 0.29 $$\lambda _{g}$$ λ g . The RF-rectifier demonstrates the capacity to effectively utilize the frequency domain by employing multi-band operation and exhibiting a good impedance bandwidth through a sequential matching technique. Thus, by effectively controlling the rectenna’s ambient performance, the proposed design holds the potential for powering a range of low-power biomedical implantable devices. (BIDs).

This paper presents a unique antenna that is designed to be efficient, with improved gain and partial flexibility, for use in wearable biomedical telemetry applications. The antenna design utilizes a semi-flexible RO5880 substrate material (dielectric constant, $\varepsilon _{r}$ = 2.2, loss tangent, ( $\tan \delta $ ) = 0.0009) with physical dimensions measuring 0.47 $\lambda _{g} \times $ 0.47 $\lambda _{g}$ . The model involves the incorporation of rectangular inverted “C” slots, which effectively results in a reduction of the resonant frequency. Additionally, a distributed rectangular slot is introduced on the ground plane, contributing to the augmentation of the operational bandwidth. The operational frequency of the proposed antenna design is 2.40 GHz, accompanied by a bandwidth (BW) of 320 MHz at a −10 dB level. This equates to a fractional percentage bandwidth (FBW) of 13.33% centered around the frequency of 2.40 GHz. The antenna design presented in this work demonstrates the preservation of improved gain and efficiency, achieving values of 3.67 dBi and 94%, respectively, at a frequency of 2.40 GHz. The work demonstrates through simulation and experimental outcomes that the antenna exhibits minimal impact on parameters such as gain reflection coefficient $(|S_{11}|)$ , BW, and bending efficiency. Furthermore, the antenna underwent simulation and experimental testing in close proximity to the human body, revealing favorable operational characteristics. The proposed antenna exhibits substantial potential as a viable option for wearable biomedical instruments. Thus, the proposed wearable antenna design in this study offers a wideband antenna for ISM band applications, expanding bandwidth without compromising performance. Bending the antenna minimally affects gain, bandwidth, and efficiency when worn on the body, making it suitable for wearables. It also maintains a reasonably low Specific Absorption Rate (SAR), reducing wave absorption by the body. Unique features like rectangular inverted “C” slots and a distributed rectangular slot on the ground plane enhance bandwidth while maintaining performance during bending.

Abstract Background Radiology serves in the diagnosis and management of many diseases. Despite its rising importance and use, radiology is not a core component of a lot of medical school curricula. This survey aims to clarify current gaps in the radiological education in Egyptian medical schools. In February–May 2021, 5318 students enrolled in Egyptian medical schools were recruited and given a 20-multiple-choice-question survey assessing their radiology knowledge, radiograph interpretation, and encountered imaging experiences. We measured the objective parameters as a percentage. We conducted descriptive analysis and used Likert scales where values were represented as numerical values. Percentages were graphed afterwards. Results A total of 5318 medical students in Egypt answered our survey. Gender distribution was 45% males and 54% females. The results represented all 7 class years of medical school (six academic years and a final training year). In assessing students’ knowledge of radiology, most students (75%) reported that they received ‘too little’ education, while 20% stated the amount was ‘just right’ and only 4% reported it was ‘too much.’ Sixty-two percent of students stated they were taught radiology through medical imaging lectures. Participants’ future career plans were almost equally distributed. Near half of participants (43%) have not heard about the American College of Radiology Appropriateness Criteria (ACR-AR), while 39% have heard about it but are not familiar with. Conclusions Radiology is a novel underestimated field. Therefore, medical students need more imaging exposure. To accomplish this, attention and efforts should be directed toward undergraduate radiology education to dissolve the gap between radiology and other specialties during clinical practice. A survey answered by medical students can bridge between presence of any current defect in undergraduate radiology teaching and future solutions for this topic.

Abstract Background There is a worldwide deficit in teaching and training in the field of radiology for undergraduate medical students. This educational gap is prominent in many medical schools as most radiology curricula are a part of other specialty trainings, usually provided by non-radiologists. After COVID-19 pandemic, there was an increased trend in online education. However, questions have been raised about the efficacy and acceptance of online education. We developed a course on the principles of radiology and medical imaging basics to target Egyptian medical students. We then assessed the impact of these educational videos through several online surveys. Our "The Principles of Radiology Online Course" was delivered to students at various Egyptian medical schools; it was a prerecorded series composed of nine sessions, and each session followed the sequence of a pre-test, video, and post-test. There was a final survey to assess the overall feedback. Finally, we analyzed the results to give insight onto how teaching radiology through online lectures can help build better physicians. Results Among various medical schools around Egypt, 1396 Egyptian medical students joined this cohort. Cohort population percentage was 56% female and 44% male. Ninety-eight percent of the students agreed that this program increased their understanding of radiology. Eighty-four percent of the students found the platform friendly and easy to use. Seventy-nine percent found these webinars were more convenient compared to in-person education. Statistical significance (p-value

Abstract Background In multidisciplinary education, different perspectives from more than one discipline are used to illustrate a certain topic. The aim of this study was to evaluate the effectiveness of an online, multidisciplinary radiology curriculum to teach radiology to medical students in Egypt. A multidisciplinary team of radiologists, surgeons, and internists taught a series of 5 case-based radiology sessions on a web conference platform. Topics included common clinical case scenarios for various body systems. Undergraduate medical students across Egypt were enrolled in the course. A pre-test–post-test design was used to evaluate the efficacy of each session. Upon course completion, students filled out a subjective survey to assess the radiology education series. Results On average, 1000 students attended each session. For each session, an average of 734 students completed both the pre-test and post-test. There was a statistically significant increase in post-test scores compared to pre-test scores across all 5 sessions (p

In the era of digital microscopic imaging, Image Processing, data analysis, classification, decision support systems have emerged as one of the most important tools for diagnostic research. Physicians can observe cellular internal structures abnormalities by visualizing and analyzing images. Leukemia is a malignant disease characterized by the uncontrolled accumulation of abnormal white blood cells. The recognition of acute leukemia blast cells in colored microscopic images is a challenging task. The first important step in the automatic recognition of this disease, image segmentation, is considered to be the most critical step. In this study, we present a decision support system that includes the panel selection, segmentation using K-means clustering to identify the leukemia cells and features extraction, and image refinement. After the decision support system successfully identifies the cells and its internal structure, the cells are classified according to their morphological features of this analysis the decision support system was tested using a public dataset designed to test segmentation techniques for identifying specific cells, and the results of this analysis were compared with those of other techniques, which were suggested by other researchers, applied to the same data. The algorithm was then applied to another dataset, extracted under the supervision by an expert pathologist, from a local hospital; the total dataset consisted of 757 images gathered from two datasets. The images of the datasets are labeled with three different labels, which represents three types of leukemia cells: blast, myelocyte, and segmented cells. The process of labeling of these images was revised by the expert pathologist. The algorithm testing using this dataset demonstrated an overall accuracy of 99.517%, the sensitivity of 99.348%, and specificity of 99.529%. Therefore, this algorithm yielded promising results and warrants further research. Keywords: Decision support system, Leukaemia, Image processing, Classification