Microwave Ablation for Osteoid Osteoma in a Young Patient: A Case Report.

Osteoid osteoma (OO) is a common benign ossifying lesion that is most prevalent among youth. Usually, it attacks the diaphyseal or metaphyseal bones that are tubular. The common hallmark of muscle pain is the reported occurrence of night pain that is nearly always present, yields satisfactory responses from nonsteroidal anti-inflammatory medications, and may be joined by complaints regarding physical activities. Also, it shows typical signs of study procedures like computed tomography (CT) and magnetic resonance imaging (MRI). A nidus, which is the primary marker in the diagnostic formation of shadowed images, is a crucial sign of an OO. This source is usually portrayed as an oval lytic lesion, measuring 1 cm flat and surrounded by a region of reactive ossification. It is laborious to diagnose OO since the condition is frequently confused with many other ones, and testing and therapy may be delayed and complicated as a result. There are still few studies on OO diagnosis and distinguishing of surrogate conditions. Unfortunately, either ablation or resection can be said to be the cure. Improved detection of OO shows the possibility for prompt diagnosis, fewer patient discomfort and side effects, less cost involved in unnecessary treatments, and a rightly diagnosed condition.

Artificial Intelligence Applications for Biomedical Cancer Research: A Review.

Artificial intelligence (AI) has rapidly evolved and demonstrated its potential in transforming biomedical cancer research, offering innovative solutions for cancer diagnosis, treatment, and overall patient care. Over the past two decades, AI has played a pivotal role in revolutionizing various facets of cancer clinical research. In this comprehensive review, we delve into the diverse applications of AI across the cancer care continuum, encompassing radiodiagnosis, radiotherapy, chemotherapy, immunotherapy, targeted therapy, surgery, and nanotechnology. AI has revolutionized cancer diagnosis, enabling early detection and precise characterization through advanced image analysis techniques. In radiodiagnosis, AI-driven algorithms enhance the accuracy of medical imaging, making it an invaluable tool for clinicians in the detection and assessment of cancer. AI has also revolutionized radiotherapy, facilitating precise tumor boundary delineation, optimizing treatment planning, and enabling real-time adjustments to improve therapeutic outcomes while minimizing collateral damage to healthy tissues. In chemotherapy, AI models have emerged as powerful tools for predicting patient responses to different treatment regimens, allowing for more personalized and effective strategies. In immunotherapy, AI analyzes genetic and imaging data to select ideal candidates for treatment and predict responses. Targeted therapy has seen great advancements with AI, aiding in the identification of specific molecular targets for tailored treatments. AI plays a vital role in surgery by offering real-time navigation and support, enhancing surgical precision. Moreover, the synergy between AI and nanotechnology promises the development of personalized nanomedicines, offering more efficient and targeted cancer treatments. While challenges related to data quality, interpretability, and ethical considerations persist, the future of AI in cancer research holds tremendous promise for improving patient outcomes through advanced and individualized care.

Human-Robot Collaboration for Healthcare: A Narrative Review.

Robotic applications have often quickly transitioned from industrial to social. Because of this, robots can now engage with people in a natural way and blend in with their surroundings. Due to the lack of medical professionals, growing healthcare costs, and the exponential rise in the population of vulnerable groups like the ill, elderly, and children with developmental disabilities, the use of social robots in the healthcare system is expanding. As a result, social robots are employed in the medical field to entertain and educate hospitalized patients about health issues, as well as to assist the elderly and sick. They are also employed in the dispensing of medications, rehabilitation, and emotional and geriatric care. Thus, social robots raise the standard and effectiveness of medical care. This article explains how patients and healthcare professionals collaborate with robots in the healthcare industry. The objectives of this collaboration are to resolve moral and legal concerns, improve patient outcomes, and improve healthcare delivery. It has a broad range of uses, including telemedicine, rehabilitation, and robotic surgical support. Human-robot interaction is the term used to describe interactions between social robots and people. Many obstacles stand in the way of human-robot interaction in healthcare, including safety concerns, acceptability issues, appropriateness, usefulness, and the worry that robots may replace human carers. In the end, these difficulties result in a poor adoption rate for robotic technology. As a result, the applications and difficulties of human-robot interaction in healthcare are thoroughly evaluated in this research. This study also reviews future safety prospects from human-robot interaction in healthcare, as well as ethical and usability issues including privacy, trust, and safety, and our aims to provide a comprehensive overview of the use of robots in healthcare, including their applications, benefits, challenges, and prospects, to facilitate a deeper understanding of this evolving field.

Emerging Applications of Biomedical Science in Pandemic Prevention and Control: A Review.

The COVID-19 pandemic has made it abundantly clear how crucial biomedical science is to pandemic control and prevention on a global scale. The importance of biomedical science in the fight against pandemics has increased with the appearance of new, deadly infectious diseases. Biomedical science and engineering have been presented as possible areas for combating the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to the unique challenges raised by the pandemic, as reported by epidemiologists, immunologists, and doctors, including the survival, symptoms, protein surface composition, and infection mechanisms of COVID-19. These multidisciplinary engineering concepts are applied to design and develop prevention methods, diagnostics, monitoring, and therapies. An infectious disease outbreak that has spread over a sizable region, such as several continents or the entire world, and is affecting a sizable number of people is referred to as a "pandemic. While current knowledge about the SARS-CoV-2 virus is still limited, various (old and new) biomedical approaches have been developed and tested. Here, we review the emerging applications of biomedical science in pandemic prevention and control, including rapid diagnosis tests, the development of vaccines, antiviral therapies, artificial intelligence, genome sequencing, and personal protective equipment. Biomedical science and nanotechnology are two fields that have the potential to combine to develop emerging applications for combating pandemics. In this review, we also discuss the intersection of biomedical science and nanotechnology in pandemic prevention and control.