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Large language models (LLMs) can respond to free-text queries without being specifically trained in the task in question, causing excitement and concern about their use in healthcare settings. ChatGPT is a generative artificial intelligence (AI) chatbot produced through sophisticated fine-tuning of an LLM, and other tools are emerging through similar developmental processes. Here we outline how LLM applications such as ChatGPT are developed, and we discuss how they are being leveraged in clinical settings. We consider the strengths and limitations of LLMs and their potential to improve the efficiency and effectiveness of clinical, educational and research work in medicine. LLM chatbots have already been deployed in a range of biomedical contexts, with impressive but mixed results. This review acts as a primer for interested clinicians, who will determine if and how LLM technology is used in healthcare for the benefit of patients and practitioners. This review explains how large language models (LLMs), such as ChatGPT, are developed and discusses their strengths and limitations in the context of potential clinical applications.

As the burgeoning field of Artificial Intelligence (AI) continues to permeate the fabric of healthcare, particularly in the realms of patient surveillance and telemedicine, a transformative era beckons. This manuscript endeavors to unravel the intricacies of recent AI advancements and their profound implications for reconceptualizing the delivery of medical care. Through the introduction of innovative instruments such as virtual assistant chatbots, wearable monitoring devices, predictive analytic models, personalized treatment regimens, and automated appointment systems, AI is not only amplifying the quality of care but also empowering patients and fostering a more interactive dynamic between the patient and the healthcare provider. Yet, this progressive infiltration of AI into the healthcare sphere grapples with a plethora of challenges hitherto unseen. The exigent issues of data security and privacy, the specter of algorithmic bias, the requisite adaptability of regulatory frameworks, and the matter of patient acceptance and trust in AI solutions demand immediate and thoughtful resolution .The importance of establishing stringent and far-reaching policies, ensuring technological impartiality, and cultivating patient confidence is paramount to ensure that AI-driven enhancements in healthcare service provision remain both ethically sound and efficient. In conclusion, we advocate for an expansion of research efforts aimed at navigating the ethical complexities inherent to a technology-evolving landscape, catalyzing policy innovation, and devising AI applications that are not only clinically effective but also earn the trust of the patient populace. By melding expertise across disciplines, we stand at the threshold of an era wherein AI's role in healthcare is both ethically unimpeachable and conducive to elevating the global health quotient.

Key Points Medical 3D printing refers to the fabrication of anatomical structures, typically derived from volumetric medical image data, and enables visual inspection and direct manipulation of hand-held models of human anatomy and pathology In cardiovascular 3D printing, advanced modern imaging such CT and MR is combined with dedicated 3D printing software and hardware Cardiovascular 3D printing enhances the diagnostic work-up of complex cardiovascular diseases, as well as surgical and interventional procedural planning and simulation 3D printing improves patient engagement in understanding their own diseases and participating in their own decision-making, and improves communication with patients and their families Widespread adoption of 3D printing is currently limited by the lack of robust evidence that systematically demonstrates effectiveness, and by the high costs and workflow complexity Cardiovascular 3D bioprinting and molecular 3D printing — which combine advanced manufacturing, cell biology, molecular biomarkers, and materials science — have not yet translated into clinical practice, but hold great promise for the future 3D printing applications for cardiovascular care range from models for education to planning and simulation of interventions and the generation of implantable devices. This Review summarizes the current cardiovascular 3D printing strategies and applications, including the workflow from image acquisition to the generation of a hand-held model, and highlights the future perspectives of cardiovascular 3D printing. 3D-printed models fabricated from CT, MRI, or echocardiography data provide the advantage of haptic feedback, direct manipulation, and enhanced understanding of cardiovascular anatomy and underlying pathologies. Reported applications of cardiovascular 3D printing span from diagnostic assistance and optimization of management algorithms in complex cardiovascular diseases, to planning and simulating surgical and interventional procedures. The technology has been used in practically the entire range of structural, valvular, and congenital heart diseases, and the added-value of 3D printing is established. Patient-specific implants and custom-made devices can be designed, produced, and tested, thus opening new horizons in personalized patient care and cardiovascular research. Physicians and trainees can better elucidate anatomical abnormalities with the use of 3D-printed models, and communication with patients is markedly improved. Cardiovascular 3D bioprinting and molecular 3D printing, although currently not translated into clinical practice, hold revolutionary potential. 3D printing is expected to have a broad influence in cardiovascular care, and will prove pivotal for the future generation of cardiovascular imagers and care providers. In this Review, we summarize the cardiovascular 3D printing workflow, from image acquisition to the generation of a hand-held model, and discuss the cardiovascular applications and the current status and future perspectives of cardiovascular 3D printing.

Extensive evidence underscores the pivotal role of socioeconomic status (SES) in shaping cancer-related outcomes. However, synthesizing definitive and actionable insights from the expansive body of literature remains a significant challenge. To elucidate the associations between SES, cancer outcomes, and the overall cancer burden, we conducted a comprehensive burden estimation coupled with an umbrella review of relevant meta-analyses. Our findings reveal that robust or highly suggestive meta-analytic evidence supports only a limited number of these associations. Individuals with lower SES, compared to those with higher SES, are disproportionately disadvantaged by reduced access to immunotherapy, KRAS testing for colorectal cancer, targeted cancer therapies, and precision treatments for melanoma. Additionally, they exhibit lower rates of breast cancer screening and higher incidence rates of lung cancer. Furthermore, countries with a higher Human Development Index demonstrate a substantially greater burden related cancer incidence, with this disparity being more pronounced among men than women. Socioeconomic status has been previously linked to cancer outcomes. Here, the authors use an umbrella review to identify differences in access to immunotherapy and cancer screening.

Objective Lifestyle interventions are effective, but those delivered via in-person group meetings have poor scalability and reach. Research is needed to establish if remotely delivered lifestyle interventions are non-inferior to in-person delivered lifestyle interventions. Methods We conducted a randomized non-inferiority trial ( N  = 329) to compare a lifestyle intervention delivered remotely and asynchronously via an online social network (Get Social condition) to one delivered via in-person groups (Traditional condition). We hypothesized that the Get Social condition would result in a mean percent weight loss at 12 months that was not inferior to the Traditional condition. Additional outcomes included intervention delivery costs per pound lost and acceptability (e.g., convenience, support, modality preferences). Results At 12 months, no significant difference in percent weight change was observed between the Get Social and Traditional conditions (2.7% vs. 3.7%, p  = 0.17) however, criteria for non-inferiority were not met. The Get Social condition costs $21.45 per pound lost versus $26.24 for the Traditional condition. A greater percentage of Get Social condition participants rated participation as convenient (65% vs 44%; p  = 0.001). Conclusions Results revealed a remotely-delivered asynchronous lifestyle intervention resulted in slightly less weight loss than an in-person version but may be more economical and convenient. Trial registration ClinicalTrials.gov NCT02646618; https://clinicaltrials.gov/ct2/show/NCT02646618 .

Reception is an essential process for patients seeking medical care and a critical component influencing the healthcare experience. However, current communication systems rely mainly on human efforts, which are both labor and knowledge intensive. A promising alternative is to leverage the capabilities of large language models (LLMs) to assist the communication in medical center reception sites. Here we curated a unique dataset comprising 35,418 cases of real-world conversation audio corpus between outpatients and receptionist nurses from 10 reception sites across two medical centers, to develop a site-specific prompt engineering chatbot (SSPEC). The SSPEC efficiently resolved patient queries, with a higher proportion of queries addressed in fewer rounds of queries and responses (Q 68.0% ≤2 rounds) compared with nurse-led sessions (50.5% ≤2 rounds) ( P  = 0.009) across administrative, triaging and primary care concerns. We then established a nurse–SSPEC collaboration model, overseeing the uncertainties encountered during the real-world deployment. In a single-center randomized controlled trial involving 2,164 participants, the primary endpoint indicated that the nurse–SSPEC collaboration model received higher satisfaction feedback from patients (3.91 ± 0.90 versus 3.39 ± 1.15 in the nurse group, P  < 0.001). Key secondary outcomes indicated reduced rate of repeated Q&R (3.2% versus 14.4% in the nurse group, P  < 0.001) and reduced negative emotions during visits (2.4% versus 7.8% in the nurse group, P  < 0.001) and enhanced response quality in terms of integrity (4.37 ± 0.95 versus 3.42 ± 1.22 in the nurse group, P  < 0.001), empathy (4.14 ± 0.98 versus 3.27 ± 1.22 in the nurse group, P  < 0.001) and readability (3.86 ± 0.95 versus 3.71 ± 1.07 in the nurse group, P  = 0.006). Overall, our study supports the feasibility of integrating LLMs into the daily hospital workflow and introduces a paradigm for improving communication that benefits both patients and nurses. Chinese Clinical Trial Registry identifier: ChiCTR2300077245 . In a randomized controlled trial involving 2,185 participants, patient satisfaction was improved during interactions with receptionist nurses when assisted by a large language model, with significant reductions in negative emotions and repeated questions.

Since the introduction of widely available e-scooter rentals in Hamburg, Germany in June of 2019, our emergency department has seen a sharp increase in the amount of e-scooter related injuries. Despite a rising number of studies certain aspects of e-scooter mobility remain unclear. This study examines the various aspects of e-scooter associated injuries with one of the largest cohorts to date. Electronic patient records of emergency department admissions were screened for e-scooter associated injuries between June 2019 and December 2021. Patient demographic data, mechanism of injury, alcohol consumption, helmet usage, sustained injuries and utilized medical resources were recorded. Overall, 268 patients (57% male) with a median age of 30.3 years (IQR 23.3; 40.0) were included. 252 (94%) were e-scooter riders themselves, while 16 (6%) were involved in crashes associated with an e-scooter. Patients in non-rider e-scooter crashes were either cyclists who collided with e-scooter riders or older pedestrians (median age 61.2 years) who tripped over parked e-scooters. While e-scooter riders involved in a crash sustained an impact to the head or face in 58% of cases, those under the influence of alcohol fell on their head or face in 84% of cases. This resulted in a large amount of maxillofacial soft tissue lacerations and fractures. Extremity fractures and dislocations were more often recorded for the upper extremities. This study comprises one of the largest cohorts of e-scooter associated injuries to date. Older pedestrians are at risk to stumble over parked e-scooters. E-scooter crashes with riders who consumed alcohol were associated with more severe injuries, especially to the head and face. Restricted e-scooter parking, enforcement of drunk driving laws for e-scooters, and helmet usage should be recommended.

Genetic counselling education and training in Europe spans a continuum of 30 years. More master programs are opening due the demand for qualified genetic counselors. This report describes the evolution of training in Europe and the current state of genetic counselling training programs. Directors of master programs in Europe were invited to complete an online survey describing their program, including year of commencement, course duration, number of students and frequency of intake and number graduating. Results of the survey were presented at a closed meeting at the European Society of Human Genetics conference in 2022 along with a facilitated stakeholder engagement session in which 19 professionals participated to understand the challenges in delivering genetic counselling education in Europe. A total of 10 active programs exists in Europe with the first training program starting in 1992. The majority of training programs have a 2-year duration, with just over half of programs having an annual intake of students. Up to May 2022, 710 students have graduated from genetic counseling training programs across Europe. Of these, 670 students graduated from European Board of Medical Genetics-registered programs. Arranging clinical placements, clinical and counseling supervision of students, research collaboration for MSc research projects and incorporating genomics into the curriculum were identified as current challenges for genetic counseling education. Genetic counseling is still a developing profession in Europe and this historical and current view of the European genetic counselor pathways, allows for educational and professional standards to be examined as the profession evolves into the future.

Non-adherence to medication is a global health problem with far-reaching individual-level and population-level consequences but remains unappreciated and under-addressed in the clinical setting. With increasing comorbidity and polypharmacy as well as an ageing population, cardiovascular disease and medication non-adherence are likely to become increasingly prevalent. Multiple methods for detecting non-adherence exist but are imperfect, and, despite emerging technology, a gold standard remains elusive. Non-adherence to medication is dynamic and often has multiple causes, particularly in the context of cardiovascular disease, which tends to require lifelong medication to control symptoms and risk factors in order to prevent disease progression. In this Review, we identify the causes of medication non-adherence and summarize interventions that have been proven in randomized clinical trials to be effective in improving adherence. Practical solutions and areas for future research are also proposed.In this Review, Bosworth and colleagues describe the causes of medication non-adherence, discuss interventions that have been clinically shown to improve adherence and identify areas for future research.