Medicine Format Research Articles

Three-dimensional finite element analysis of stress distribution on different complex macro designs in commercially available implants: An in-vitro study

ObjectiveThis study aimed to investigate the effects of different commercially available complex implant macro designs on stress distributions using Finite element analysis. The experiment is done under varying simulated bone conditions to provide reference for clinical application. Materials and methodsThe study employed the Finite Element Analysis (FEA) method to compare four commercially available complex implant macro designs on a Computer-Aided Design (CAD) model of a maxillary bone segment. The three-dimensional geometrical model of the implants was reconstructed from computed tomography (CT)-slices in Digital Imaging and Communications in Medicine (DICOM) format and contact condition between the implant and the bone was considered as ‘Bonded’, implying perfect osseointegration. All materials used in the models were assumed to be isotropic, homogeneous, and linearly elastic. The Finite element simulations employed load of 400 N under both axial and non-axial conditions Stresses were analysed under different bone conditions. ResultsAverage values of von Mises stresses were used for comparing stress levels between implant designs. There was a definite increase in the equivalent stress values from higher density(D1)to lower density (D4) bone conditions for all implants. The percentage of increase ranged from 23.63 to 49.39 on axial loading and 20.39 to 57.19 when subjected to non-axial loading. The equivalent stress values resulted from non-axial loading were 1.78–2.94 times higher than that of axial loading for all implants under all bone densities. Among the complex designs Equinox Myriad Plus implant exhibited the least stress under axial loading (12.749–19.046 MPa) and (37.462–49.217 MPa) for non-axial loading. The stress on the crestal module was higher (1.49–2.99 times) than the overall stress on the implant regardless of the loading direction or bone conditions. ConclusionsData from the present study shows Equinox Myriad Plus implant generating the least equivalent stress and this can be taken as indicator in the biomechanical performance of the design.

Applying a Deep Learning Model for Total Kidney Volume Measurement in Autosomal Dominant Polycystic Kidney Disease.

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary renal disease leading to end-stage renal disease. Total kidney volume (TKV) measurement has been considered as a surrogate in the evaluation of disease severity and prognostic predictor of ADPKD. However, the traditional manual measurement of TKV by medical professionals is labor-intensive, time-consuming, and human error prone. In this investigation, we conducted TKV measurements utilizing magnetic resonance imaging (MRI) data. The dataset consisted of 30 patients with ADPKD and 10 healthy individuals. To calculate TKV, we trained models using both coronal- and axial-section MRI images. The process involved extracting images in Digital Imaging and Communications in Medicine (DICOM) format, followed by augmentation and labeling. We employed a U-net model for image segmentation, generating mask images of the target areas. Subsequent post-processing steps and TKV estimation were performed based on the outputs obtained from these mask images. The average TKV, as assessed by medical professionals from the testing dataset, was 1501.84 ± 965.85 mL with axial-section images and 1740.31 ± 1172.21 mL with coronal-section images, respectively (p = 0.73). Utilizing the deep learning model, the mean TKV derived from axial- and coronal-section images was 1536.33 ± 958.68 mL and 1636.25 ± 964.67 mL, respectively (p = 0.85). The discrepancy in mean TKV between medical professionals and the deep learning model was 44.23 ± 58.69 mL with axial-section images (p = 0.8) and 329.12 ± 352.56 mL with coronal-section images (p = 0.9), respectively. The average variability in TKV measurement was 21.6% with the coronal-section model and 3.95% with the axial-section model. The axial-section model demonstrated a mean Dice Similarity Coefficient (DSC) of 0.89 ± 0.27 and an average patient-wise Jaccard coefficient of 0.86 ± 0.27, while the mean DSC and Jaccard coefficient of the coronal-section model were 0.82 ± 0.29 and 0.77 ± 0.31, respectively. The integration of deep learning into image processing and interpretation is becoming increasingly prevalent in clinical practice. In our pilot study, we conducted a comparative analysis of the performance of a deep learning model alongside corresponding axial- and coronal-section models, a comparison that has been less explored in prior research. Our findings suggest that our deep learning model for TKV measurement performs comparably to medical professionals. However, we observed that varying image orientations could introduce measurement bias. Specifically, our AI model exhibited superior performance with axial-section images compared to coronal-section images.

Numerical and Experimental Validation for Connecting Nature with Architecture by Mimicking Cranium into a Shell Roof

This study focuses on a structural element bio-mimicked from the human cranium (HC) into a shell element. As the HC is effective in resisting intracranial pressure developed by the brain, a water tank was considered to use a bio-mimicked shape of a shell as a roof. An optimized numerical model was validated experimentally and compared with a conventional specimen. The structural behavior of the bio-mimicked specimen is similar and performs more efficiently than the conventional specimen in capacity ratio, crack formation, and load-carrying capacity. Methodology followed: A Computed Tomography (CT) scan of the HC was obtained in Digital Imaging and Communications in Medicine (DICOM) format for finite element analysis (FEA). From the geometric parameters of the HC, the radius of the curvature-to-thickness ratio was derived for the shell. The span and thickness of the shell under two criteria were considered. The spherical and circular shell behaviors were found to be similar to those of the HC, whereas the elliptical shell behavior was not. We studied the shape effect of the HC with the conventional slab and found that the HC shape has an impact on the behavior and is the most efficient. A bio-mimicked mono column was considered as a supporting column for the water tank and analyzed. Overall, adopting this bio-mimicking of the HC into the shell roof connects nature with sustainable architecture.

Modeling of joint extraction of entity relationships in clinical electronic medical records

The advancement of medical informatization necessitates extracting entities and their relationships from electronic medical records. Presently, research on electronic medical records predominantly concentrates on single-entity relationship extraction. However, clinical electronic medical records frequently exhibit overlapping complex entity relationships, thereby heightening the challenge of information extraction. To rectify the absence of a clinical medical relationship extraction dataset, this study utilizes electronic medical records from 584 patients in a hospital to create a compact clinical medical relationship extraction dataset. To address the pipelined relationship extraction model’s limitation in overlooking the one-to-many correlation problem between entities and relationships, this paper introduces a cascading relationship extraction model. This model integrates the MacBERT pre-training model, gated recurrent network, and multi-head self-attention mechanism to enhance the extraction of text features. Simultaneously, adversarial learning is incorporated to bolster the model’s robustness. In scenarios involving one-to-many relationships between entities, a two-phase task is employed. Initially, the main entity is predicted, followed by predicting the associated object and their correspondences. Employing this cascade-structured approach enables the model to flexibly manage intricate entity relationships, thereby enhancing extraction accuracy. Experimental results demonstrate the model’s efficiency, yielding F1-scores of 82.8%, 76.8%, and 88.2% for fulfilling relational extraction requirements and tasks on DuIE, CHIP-CDEE, and private datasets, respectively. These scores represent improvements over the benchmark model. The findings indicate the model’s applicability in practical domains, particularly in tasks such as biomedical information extraction.

Analysis of artificial intelligence medical treatment for closed muscle skin nerve injury caused by aerobics training

In aerobics training, closed myocutaneous nerve damage needs to be paid attention to, especially high-intensity training may cause minor damage to muscles and nerves. With the help of AI medical technology and the understanding of molecular and cellular biomechanics, we can more accurately explore the mechanism of injury, such as the effects of nerve tensile stress and microenvironment changes on nerve regeneration. This helps to develop scientific rehabilitation methods, such as AI-assisted personalized training, neural regeneration technology, and real-time monitoring of training intensity to speed up athletes’ rehabilitation and reduce the risk of future injuries. Purpose: Aerobics training is very strict and requires high physical fitness of dancers. During long-term training, dancers can easily cause closed musculocutaneous nerve injury. Traditional medicine is difficult to guarantee the treatment effect of patients with musculocutaneous nerve injury. The use of artificial intelligence medicine for closed musculocutaneous nerve injury treatment can improve the treatment effect of aerobics training induced closed musculocutaneous nerve injury. Method: This article utilized artificial intelligence medicine for the treatment of musculocutaneous nerve injury, and used artificial intelligence technology to analyze patient imaging and other data to assist doctors in accurate diagnosis. Utilize intelligent algorithms to predict medication plans, reduce medication errors, and intelligently adjust the course of treatment based on the patient’s condition. In artificial intelligence healthcare, high-quality online medical services can be created through intelligent technology, providing convenient medical consultation for patients. Result: This article selected 200 patients with musculocutaneous nerve injury caused by aerobics training for grouping experiments. The average diagnostic accuracy of traditional medicine and artificial intelligence medicine were 84.2% and 95.6%, respectively. Conclusion: Artificial intelligence medicine can achieve medical informatization and intelligently analyze patients’ medical information, which helps to improve the accuracy of medical diagnosis for aerobics training injuries.

Being, becoming, and belonging: reconceptualizing professional identity formation in medicine.

Over the last decade, there has been a drive to emphasize professional identity formation in medical education. This shift has had important and positive implications for the education of physicians. However, the increasing recognition of longstanding structural inequalities within society and the profession has highlighted how conceptualizations of professional identity formation have also had unintended harmful consequences. These include experiences of identity threat and exclusion, and the promotion of norms and values that over-emphasize the preferences of culturally dominant groups. In this paper, the authors put forth a reconceptualization of the process of professional identity formation in medicine through the elaboration of 3 schematic representations. Evolutions in the understandings of professional identity formation, as described in this paper, include re-defining socialization as an active process involving critical engagement with professional norms, emphasizing the role of agency, and recognizing the importance of belonging or exclusion on one's sense of professional self. The authors have framed their analysis as an evidence-informed educational guide with the aim of supporting the development of identities which embrace diverse ways of being, becoming, and belonging within the profession, while simultaneously upholding the standards required for the profession to meet its obligations to patients and society.

Evidence of age segregation behavior in Hypacrosaurus stebingeri (Hadrosauridae: Lambeosaurinae) based on the taphonomic comparison of bonebeds from the Upper Cretaceous (upper Campanian) Oldman Formation of southernmost Alberta (Canada) and Two Medicine Formation of Montana (USA)

Hadrosaurid social structure is still poorly understood. Evidence from bonebeds suggests that juvenile individuals of some hadrosaurid species lived apart from herds composed of older individuals, a phenomenon called age segregation. However, the timing at which juvenile individuals became segregated and later rejoined a multigenerational herd is unknown. Three monodominant bonebeds that preserve the remains of multiple individuals of the lambeosaurine hadrosaurid Hypacrosaurus stebingeri at different ontogenetic stages offer an opportunity to better understand the social structure of this species: the Devil's Coulee juvenile hadrosaur bonebed (JBB) from the Oldman Formation of Alberta (Canada) preserves a minimum of four similar-sized late juvenile individuals; the Blacktail Creek North (BCNB) bonebed from the Two Medicine Formation of Montana (USA) preserves a minimum of 23 early juvenile (previously referred to as “nestling”) individuals; and the Lambeosite (LB) bonebed preserves four similar-sized late juvenile individuals and one adult individual. These bonebeds show uniform taphonomic signatures throughout their respective bone assemblages, characterized by little to no weathering and abrasion, uniform style of fracturing, and rare tooth marks on bones. All three bonebeds are interpreted as mass-mortality assemblages. Histological data indicate that the late juvenile individuals from the JBB were three years old at the time of death, similar to the slightly larger late juvenile individuals from the LB, whereas the early juveniles from the BCNB had not yet reached 1 year of age. A taphonomic comparison of the three bonebeds reveal that H. stebingeri individuals lived in age-segregated groups, likely cohorts, until into their fourth year of life when, after having reached sexual maturity, they rejoined a multigenerational herd. The smaller number of individuals preserved in bonebeds representing later ontogenetic stages could reflect a decrease in group size due to high juvenile mortality rate or to higher metabolic needs.

Updating the Upper Cretaceous (Campanian) Two Medicine Formation of Montana: Lithostratigraphic revisions, new CA-ID-TIMS U-Pb ages, and a calibrated framework for dinosaur occurrences

The Campanian Two Medicine Formation of northwestern Montana, USA, is richly fossiliferous, and discoveries made within the unit over the past century have greatly advanced our appreciation of dinosaur paleobiology and evolution. Previously undifferentiated from a lithostratigraphic perspective, the formation is now subdivided into four new members that include (from base to top) (1) the Rock City Member, (2) the Shields Crossing Member, (3) the Hagans Crossing Member, and (4) the Flag Butte Member. These new formal units and their associated fossil occurrences are also now included in an age model founded on eight high-resolution chemical abrasion−isotope dilution−thermal ionization mass spectrometry (CA-ID-TIMS) U-Pb ages. New age data confirm that the Two Medicine Formation accumulated during much of the Campanian, with deposition spanning ca. 82.4 Ma to 74.4 Ma. New age data further indicate that a major reorganization of depositional systems, marked by a shift from predominantly lacustrine to alluvial facies and accompanied by a dramatic increase in accommodation, transpired near the base of the new Flag Butte Member at ca. 76.3 Ma. This change in depositional regime correlates in age with the Judith River−Belly River discontinuity, which marks the contact between the McClelland Ferry and Coal Ridge Members in the Judith River Formation and coincides with the onset of the Bearpaw transgression in north-central Montana. The new lithostratigraphic and chronostratigraphic framework for the Two Medicine Formation serves to contextualize and calibrate the formation’s rich dinosaur fossil record, which can now be interrogated with increased clarity and precision. These results also provide ground truth for numerical models that explore the structure of the fossil record in relation to alluvial architecture and terrestrial sequence stratigraphy.

CT scan-based 3D fracture mapping in civilian gunshot intracapsular fractures of the femur neck.

IntroductionDisplaced intracapsular neck of femur (NOF) fractures secondary to civilian gunshots are rare injuries with universally poor outcomes following surgical fixation. No studies have been published on fracture mapping in NOF fractures secondary to civilian gunshots. ObjectivesWe performed CT scan-based fracture mapping to identify the most common fracture patterns in these injuries. MethodsDesign: Retrospective search of prospectively collected data. Setting: Single Level 1 Trauma hospital. Patient selection criteria: All patients presenting with gunshot fractures to the femur neck between 01 January 2009 and 31 December 2022 were identified. Once identified from Picture Archiving and Communication System (PACS), computed tomography (CT) scans in Digital Imaging and Communication in Medicine (DICOM) format were imported into Mimics 16 software and fracture fragments were segmented and three-dimensional (3D) reconstruction was generated. The reduced fractures were exported to 3-Matic software to merge the fragments and adjust the orientation in three planes. An uninjured femur model was used as a template for reduction. Fracture lines and heat maps were then generated. Our outcome measures were successful mapping of the identified fracture lines. ResultsA total of 25 intracapsular femur neck fractures were identified and suitable for CT scan mapping. All patients were male with an average age of 22 (range 18-32). Once generated, fracture maps were used to show the location, distribution and frequency of the fracture lines. In all but two cases the fracture line propagation remained within the confines of the hip joint capsule. In three cases there was fracture extension into the superior aspect of the femur head, and in one case extension into the inferior aspect. ConclusionThis is the first study to perform 3D fracture mapping for intracapsular femur neck fractures secondary to civilian gunshot injuries. The exercise has helped us better understand the commonest fracture patterns and assisted us with surgical planning and execution.

A Cost-Affordable Methodology of 3D Printing of Bone Fractures Using DICOM Files in Traumatology

Three-dimensional (3D) printing has gained popularity across various domains but remains less integrated into medical surgery due to its complexity. Existing literature primarily discusses specific applications, with limited detailed guidance on the entire process. The methodological details of converting Computed Tomography (CT) images into 3D models are often found in amateur 3D printing forums rather than scientific literature. To address this gap, we present a comprehensive methodology for converting CT images of bone fractures into 3D-printed models. This involves transferring files in Digital Imaging and Communications in Medicine (DICOM) format to stereolithography format, processing the 3D model, and preparing it for printing. Our methodology outlines step-by-step guidelines, time estimates, and software recommendations, prioritizing free open-source tools. We also share our practical experience and outcomes, including the successful creation of 72 models for surgical planning, patient education, and teaching. Although there are challenges associated with utilizing 3D printing in surgery, such as the requirement for specialized expertise and equipment, the advantages in surgical planning, patient education, and improved outcomes are evident. Further studies are warranted to refine and standardize these methodologies for broader adoption in medical practice.

Проблема критериев приемлемости в биомедицинском эксперименте: философско-методологический анализ

Introduction. The formation and development of modern evidence-based medicine is not possible without clinical studies with the participation of humans as subjects. The methodology of such experiments is based on careful selection of subjects based on the so-called eligibility criteria – parameters which form the optimal patient group for studying the therapeutic properties of a particular drug based on the science community’s expectations. The article considers some bioethical aspects of the practical problems of formulating such criteria, and also it examines the question of the possibility of proper application of scientific data obtained in the framework of clinical studies. Theoretical analysis. Based on the example of HIV-positive patients, it is shown that excessive formalization of the process of determining eligibility criteria leads to the formation of fundamental differences between participants in clinical trials and patients in routine medical practice, which put at risk the ability to properly extrapolate the results of such studies outside the experimental field and realization of one of the basic bioethical principles of clinical trials: to be useful for society. Conclusion. The article substantiates the need to revise the methodological and bioethical foundations of the process of formulating eligibility criteria, taking into account the risks faced by patients of experimental therapy and patients in real clinical practice.

A Review of Blockchain-Based Research on E-Health Data Sharing

With the development of medical data informatization, the data security, data privacy, and data controllability of electronic medical data with patient's personal privacy have gained social attention. Blockchain technology has decentralized characteristics, and the development of blockchain technology provides an effective solution for the secure sharing of e-medical data. Many scholars have proposed e-medical data security sharing solutions based on blockchain technology, and these solutions have attempted to solve the security problems encountered in sharing traditional e-medical data. By summarizing and analyzing the schemes in this field, this study analyzes the advantages, disadvantages, and challenges that the current mainstream schemes have, mainly in terms of blockchain data security storage, access control security sharing, and so on, in order to promote the further development of the e-medical data security sharing scheme based on blockchain technology. This study analyzes the blockchain-based e-medical data security sharing scheme proposed by scholars by analyzing the blockchain technology, cryptography technology, smart contract technology, P2P network technology and other related topics. Through systematic analysis and comparison, it explores the challenges of the current research and provides references for the future proposals of blockchain technology-based schemes.

Research on the status and development of medical and public health informatization in China, from the perspective of medical and preventive integration

Medical and preventive integration effectively bridges the gap between "treating diseases" and "preventing diseases". Over the years, medical and preventive integration research has focused on chronic and chronic infectious diseases, with insufficient attention to acute ones. Confronting newly emerging infectious diseases establishing continuous monitoring, early warning, emergency response, and appropriate treatment will be a key focus for developing and reforming the healthcare system. Interoperability and sharing of medical and health data are essential prerequisites for bridging the gap between medical treatment and disease prevention and are also important for promoting intelligent surveillance and early warning of infectious diseases. Informatization is necessary to achieve efficient collaboration between medical treatment and disease prevention. Reviewing the development of medical and health informatization in the United States and Europe, this paper compares and discusses the problems and challenges in developing medical and health informatization in China. The aim is to provide references for the development of medical and health informatization and the innovation of medical and preventive integration mechanisms in the country.

Gender Estimation from Morphometric Measurements of Mandibular Lingula by Using Machine Learning Algorithms and Artificial Neural Networks

Background: Sex determination from the bones is of great importance for forensic medicine and anthropology. The mandible is highly valued because it is the strongest, largest and most dimorphic bone in the skull. Aim: Our aim in this study is gender estimation with morphometric measurements taken from mandibular lingula, an important structure on the mandible, by using machine learning algorithms and artificial neural networks. Methods: Cone beam computed tomography images of the mandibular lingula were obtained by retrospective scanning from the Picture Archiving Communication Systems of the Department of Oral, Dental and Maxillofacial Radiology, Faculty of Dentistry, İnönü University. Images scanned in Digital Imaging and Communications in Medicine (DICOM) format were transferred to RadiAnt DICOM Viewer (Version: 2020.2). The images were converted to 3-D format by using the 3D Volume Rendering console of the program. Eight anthropometric parameters were measured bilaterally from these 3-D images based on the mandibular lingula. Results: The results of the machine learning algorithms analyzed showed that the highest accuracy was 0.88 with Random Forest and Gaussian Naive Bayes algorithm. Accuracy rates of other parameters ranged between 0.78 and 0.88. Conclusions: As a result of the study, it is thought that mandibular lingula-centered morphometric measurements can be used for gender determination as well as bones such as the pelvis and skull as they were found to be highly accurate. This study also provides information on the anatomical position of the lingula according to gender in Turkish society. The results can be important for oral-dental surgeons, anthropologists, and forensic experts.

The development of direct 3-dimensional printing of patient-specific mitral valve in soft material for simulation and procedural planning

ObjectivesReplicating 3-dimensional prints of patient-specific mitral valves in soft materials is a cumbersome and time-consuming process. The aim of this study was to develop a method for a direct 3-dimensional printing of patient-specific mitral valves in soft material for simulation-based training and procedural planning. MethodsA process was developed based on data acquisition using 3-dimensional transesophageal echocardiography Cartesian Digital Imaging and Communication of Medicine format, image processing using software (Vesalius3D, Blender, Meshlab, Atum3D Operation Station), and 3-dimensional printing using digital light processing, an additive manufacturing process based on photopolymer resins. Experiments involved adjustment of 3 variables: curing times, model thinness, and lattice structuring during the printing process. Printed models were evaluated for suitability in physical simulation by an experienced mitral valve surgeon. ResultsDirect 3-dimensional printing of a patient's mitral valve in soft material was completed within a range of 1.5 to 4.5 hours. Prints with postcuring times of 5, 7, 10, and 15 minutes resulted in increased stiffness. The mitral valves with 2.0-mm and 2.4-mm thinner leaflets felt more flexible without tear of the sutures through the material. The addition of lattice structures made the prints more compliant and better supported suturing. ConclusionsDirect 3-dimensional printing of a realistic and flexible patient-specific mitral valve was achieved within a few hours. A combination of thinner leaflets, reduced curing time, and lattice structures enabled the creation of a realistic patient-specific mitral valve in soft material for physical simulation.

ПЕРВЫЕ НАЦИОНАЛЬНЫЕ МЕДИЦИНСКИЕ КАДРЫ КАБАРДЫ И БАЛКАРИИ

сurrently, the study of the historical stages of the formation and development of medical personnel and the entire health care systemas a whole is one of the most relevant areas in the course of higher medical education. The significance of the problem makes us turn to the lessons of the past, namely, the history of the appearance of the first doctors, whose names and experience formed the basis for the formation and development of healthcare. The article attempts to restore the names of unfairly "forgotten" people who devoted themselves entirely to the cause of healing, as well as the history of the first national medical personnel in the region and their contribution to the prevention and treatment of the local population of the Nalchik district. The article is based on the biographical data carefully collected in the Archive Service of the Kabardino-Balkar Republic and other sources of the first well - known regional doctors from the indigenous inhabitants of Kabardino-Balkaria, as well as their contribution to the development of medical services in the region, which makes the work unique. The selfless work of the first doctors shows the history of the formation and development of traditional medicine and all health care in the Nalchik district of the Terek region in the pre-revolutionary period. Studying the history of regional healthcare development helps to better understand and evaluate positive experiences, and to anticipate the main directionsof its subsequent development.

Expert recommendation for real-world study on the application of human papillomavirus vaccine in the Yangtze River Delta region

Cervical cancer has become a global public health problem that poses a serious threat to women's health. Human papillomavirus (HPV) vaccination is an important primary preventive measure for cervical cancer. With the accelerated application of the HPV vaccine in China, conducting real-world studies (RWS) on the application of HPV vaccines can guide the rational use of the vaccine, which is of great significance for the strategy and practice of accelerating the elimination of cervical cancer in China. The Yangtze River Delta Cervical Cancer and Female Lower Genital Tract Infection Prevention and Control Alliance and Yangtze River Delta Immunization Integration Working Group organized an expert group to develop the "Expert recommendation for real-world study on the application of HPV vaccine in the Yangtze River Delta region". Based on the current situation of medical informatization and HPV vaccination administration in China, as well as literature and cases from domestic and international studies, this study describes the data chain of HPV vaccination and evaluation, introduces the study design, study direction, database construction, data governance and statistical analysis of RWS, and provides expert recommendation on the problems in carrying out the practice of HPV vaccine RWS, aiming to guide the RWS of HPV vaccine application and promote the generation of real-world evidence (RWE) in China.

Insights into discrepancies in professional identities and role models in undergraduate medical education in the context of affective burden.

International evidence strongly suggests that medical students are at high risk of mental health problems. This distress, which can be mediated by a variety of individual, interpersonal and contextual factors within the curriculum, can be mitigated by effective coping strategies and interventions. Central to this discourse is the recognition that the challenges of professional identity formation can contribute significantly to medical students' distress. The focus of our study is therefore to examine discrepancies in professional identities and role models in undergraduate medical education in relation to affective burden. Medical students at different stages of university education and high school graduates intending to study medicine were surveyed in a cross-sectional study. The study employed Osgood and Hofstätter's polarity profile to evaluate the self-image of participants, the image of an ideal and real physician, and their correlation with depression (PHQ-9) and anxiety (GAD-7). Out of the 1535 students recruited, 1169 (76.2%) participated in the study. Students rated their self-image as somewhere between a more critical real image of physicians and a more positive ideal image. Medical students at all training levels consistently rated the ideal image as remaining constant. Significant correlations were found between the professional role models of medical students and affective symptoms, particularly for the discrepancy between the ideal image of a physician and their self-image. Furthermore, 17% and nearly 15% reported significant symptoms of depression and anxiety, respectively. Our study adds to the growing body of knowledge on professional identity formation in medicine and socialisation in the medical environment. The study highlights the importance of discrepancies between self-image and ideal image in the experience of depressive and anxiety symptoms. Primary prevention-oriented approaches should incorporate these findings to promote reflective competence in relation to professional role models and strengthen the resilience of upcoming physicians in medical training.

Hospital Medical Behaviour Supervision and Operational Efficiency Evaluation Method based based on Big Data Platform

The application of cloud computing and big data core technologies and concepts to medical informatization can improve its flexibility and efficiency, and achieve the overall deployment and intensive management of the system. In the era of big data, the use of information management platform can optimize and standardize clinical diagnosis and treatment process, improve the quality and efficiency of diagnosis and treatment services, and improve the quality and level of scientific research, which meets the requirements of medical reform for fine management of hospitals and precise medical treatment in the era of evidence-based medicine. This paper introduces the development and application of big data analysis in the field of information technology. Through the research on the supervision of hospital medical service behavior, the top-level design is used to standardize the content of medical behavior supervision, and the effectiveness of supervision is discussed to achieve the purpose of reducing clinical paperwork. Based on the needs, the medical service behavior supervision system is proposed and constructed. Strengthen hospital medical behavior supervision through hospital big data analysis and knowledge base system support. This system can provide management with an effective monitoring and management tool, enabling them to promptly identify and solve problems that arise in medical services. By analyzing a large amount of medical data, hospitals can help predict the trend of disease occurrence in advance, thereby taking preventive and control measures in advance, and reducing the occurrence and spread of diseases. Through deep learning and analysis of patient data, personalized treatment plans can be provided for each patient to improve treatment effectiveness.

Deep Neural Network Based Disease Prediction Analysis

With the rapid development of social and economic construction as well as medical informatization, the medical industry has gradually entered the era of big data and artificial intelligence, using the medical big data accumulated in the hospital information system for pooling, modeling, analysis, and the use of neural networks can predict and determine the type of patient's disease and the source of the cause, which can not only reduce the complexity of the disease diagnostic test but also achieve the effect of predictive diagnosis, and provide theoretical basis and practical experience for the establishment, improvement and practical application of the intelligent medical system. It provides theoretical basis and practical experience for the establishment, improvement and practical application of intelligent medical system.