Abstract This study addresses the global health challenge of rectal cancer, aiming to assess the effectiveness of neoadjuvant chemoradiotherapy and its implications for treatment outcomes in 100 retrospectively analyzed patients. The cohort underwent neoadjuvant chemoradiotherapy followed by sphincter-sparing surgery, with recorded parameters including demographics, tumor stage, treatment protocol, and surgical outcomes. Results indicated tumor reduction in 80% of patients, with a 15% complication rate for sphincter-sparing surgery. Pathological examination underscored neoadjuvant treatment’s impact on tumor regression and reduced lymph node metastasis. In conclusion, the study emphasizes the demonstrated efficacy of neoadjuvant chemoradiotherapy in rectal cancer treatment, advocating for a comprehensive approach to managing this condition.

Abstract The growth of computer power is crucial for the development of contemporary information technologies. Artificial intelligence is a powerful instrument for every aspect of contemporary science, the economy, and society as a whole. Further growth in computing potential opens new prospects for biomedicine and healthcare. The promising works on quantum computing make it possible to increase computing power exponentially. While conventional computing relies on the formula with 2 n bits, the simplified vision of quantum computer power is 2 N , where N is a number of logical qubits. With thousandfold or more improvements in computing performance, there will be realistic options for quick protein, genes and other organic molecules 3D fold discoveries, empowering pharmaceutics and biomedical research. Personalized blockchain-based healthcare will become a reality. Medical imaging and instant healthcare data analysis will significantly speed up diagnostics and treatment control. Biomedical digital twin usage will give useful tools to any healthcare practitioner, with options for intraoperative AR and VR micro-manipulations. Nanoscale intrabody bots will be instantly customized and AI-controlled. The smart environment will be enriched with multiple sensors and actuators, giving real control of the air, water, food, and physical health factors. All these possibilities are quickly achievable only in the case of realistic quantum computing options. Even with the ability to reach this stage, there will be questions for the stability of post-quantum society: privacy, ethical issues, and quantum computing control uncertainty. General solutions to these queries will give clues for post-quantum healthcare.

Abstract Objective: This study investigates the efficacy and safety of epidural infiltration with drugs and an oxygen-ozone mixture for treating cervicobrachialgia due to disc-radicular conflict or on a degenerative basis, utilizing both retrospective analysis and direct visualization techniques. Methods: A retrospective study involving 10 patients treated with epidural infiltrations of an oxygen-ozone mixture and cortisone was conducted. The procedures were performed under CT guidance to ensure precise delivery and to monitor the diffusion of the injected substances. Pain levels were assessed using the Numerical Rating Scale (NRS) and treatment efficacy was evaluated based on symptom relief and reduction in NSAID intake. Results: Significant pain reduction was observed post-treatment, with median NRS scores decreasing from 9 (baseline) to 2 (follow-up), and a significant decrease in on-demand NSAID intake. Only one minor complication of a headache was reported. The study also demonstrated the ability of ozone to diffuse through the epidural adipose tissue, potentially enhancing treatment efficacy. Conclusion: The combined use of an oxygen-ozone mixture and cortisone for epidural infiltration is an effective and safe treatment for cervicobrachialgia, offering significant pain relief and minimizing the risk associated with traditional epidural injections. This technique presents a viable non-surgical option for patients suffering from disc-radicular conflict or degenerative conditions.

Abstract In this study, we utilized a convolutional neural network (CNN) trained on microscopic images encompassing the SARS-CoV-2 virus, the protozoan parasite “ plasmodium falciparum ” (causing of malaria in humans), the bacterium “ vibrio cholerae ” (which produces the cholera disease) and non-infected samples (healthy persons) to effectively classify and predict epidemics. The findings showed promising results in both classification and prediction tasks. We quantitatively compared the obtained results by using CNN with those attained employing the support vector machine. Notably, the accuracy in prediction reached 97.5% when using convolutional neural network algorithms.

Abstract Healthcare mobile applications satisfy different aims by frequently exploiting the built-in features found in smart devices. The accessibility of cloud computing upgrades the extra room, whereby substances can be stored on external servers and obtained directly from mobile devices. In this study, we use cloud computing in the mobile healthcare model to reduce the waste of time in crisis healthcare once an accident occurs and the patient operates the application. Then, the mobile application determines the patient’s location and allows him to book the closest medical center or expert in some crisis cases. Once the patient makes a reservation, he will request help from the medical center. This process includes pre-registering a patient online at a medical center to save time on patient registration. The E-Health model allows patients to review their data and the experiences of each specialist or medical center, book appointments, and seek medical advice.

Abstract Definitive diagnosis of Craniosynostosis (CS) with computed tomography (CT) is readily available, however, exposure to ionizing radiation is often a hard stop for parents and practitioners. Lowering head CT radiation exposure helps mitigate risks and improves diagnostic utilization. The purpose of the study is to quantify radiation exposure from head CT in patients with CS using a ‘new’ (ultra-low dose) protocol; compare prior standard CT protocol; summarize published reports on cumulative radiation doses from pediatric head CT scans utilizing other low-dose protocols. A retrospective study was conducted on patients undergoing surgical correction of CS, aged less than 2 years, between August 2014 and February 2022. Cumulative effective dose (CED) in mSv was calculated, descriptive statistics were performed, and mean ± SD was reported. A literature search was conducted describing cumulative radiation exposure from head CT in pediatric patients and analyzed for ionizing radiation measurements. Forty-four patients met inclusion criteria: 17 females and 27 males. Patients who obtained head CT using the ‘New’ protocol resulted in lower CED exposure of 0.32 mSv ± 0.07 compared to the prior standard protocol at 5.25 mSv ± 2.79 ( p < 0.0001). Five studies specifically investigated the reduction of ionizing radiation from CT scans in patients with CS via the utilization of low-dose CT protocols. These studies displayed overall CED values ranging from 0.015 mSv to 0.77 mSv. Our new CT protocol resulted in 94% reduction of ionizing radiation. Ultra-low dose CT protocols provide similar diagnostic data without loss of bone differentiation in CS and can be easily incorporated into the workflow of a children’s hospital.