The application of endoscopic debridement combined with metagenomic next-generation sequencing technology in primary spinal infections: a retrospective study.

Purpose: Spinal endoscopy is a novel minimally invasive spinal surgery technique used in recent years to treat various degenerative spinal diseases. Metagenomic next-generation sequencing (mNGS) is a new method for identifying infectious microorganisms in infectious diseases. We aim to evaluate the application effect of combining spinal endoscopy with mNGS in diagnosing and treating spinal infections.

Dual-Stream Attention-Based Classification Network for Tibial Plateau Fractures via Diffusion Model Augmentation and Segmentation Map Integration.

Objective: This study aimed to explore a novel method that integrates the segmentation guidance classification and the diffusion model augmentation to realize the automatic classification for tibial plateau fractures (TPFs).

Methods: YOLOv8n-cls was used to construct a baseline model on the data of 3781 patients from the Orthopedic Trauma Center of Wuhan Union Hospital. Additionally, a segmentation-guided classification approach was proposed.

Integrating blockchain technology with artificial intelligence for the diagnosis of tibial plateau fractures.

Purpose: The application of artificial intelligence (AI) in healthcare has seen widespread implementation, with numerous studies highlighting the development of robust algorithms. However, limited attention has been given to the secure utilization of raw data for medical model training, and its subsequent impact on clinical decision-making and real-world applications. This study aims to assess the feasibility and effectiveness of an advanced diagnostic model that integrates blockchain technology and AI for the identification of tibial plateau fractures (TPFs) in emergency settings.

Artificial Intelligence in Medical Metaverse: Applications, Challenges, and Future Prospects.

The medical metaverse is a combination of medicine, computer science, information technology and other cutting-edge technologies. It redefines the method of information interaction about doctor-patient communication, medical education and research through the integration of medical data, knowledge and services in a virtual environment. Artificial intelligence (AI) is a discipline that uses computer technology to study and develop human intelligence.

Application and Prospects of Deep Learning Technology in Fracture Diagnosis.

Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathematics, and several other fields. Recently, with the rapid development of machine learning (ML) and deep learning (DL), significant progress has been made in the field of AI. As one of the fastest-growing branches, DL can effectively extract features from big data and optimize the performance of various tasks.

Performance Assessment of GPT 4.0 on the Japanese Medical Licensing Examination.

Objective: To evaluate the accuracy and parsing ability of GPT 4.0 for Japanese medical practitioner qualification examinations in a multidimensional way to investigate its response accuracy and comprehensiveness to medical knowledge.

Methods: We evaluated the performance of the GPT 4.

Does a Video-Based and 3D Animation Hybrid Learning System Improve Teaching Outcomes in Orthopedic Surgery? A Randomized Controlled Trial.

Objective: This study aims to evaluate the instructional efficacy of a 3D Surgical Training System (3DSTS), which combines real surgical footage with high-definition 3D animations, against conventional surgical videos and textbooks in the context of orthopedic proximal humerus fracture surgeries.

Design: Before the experiment, 89 participants completed a pre-educational knowledge assessment. They were then randomized into 3 groups: the 3DSTS group (n = 30), the surgical video (SV) group (n = 29), and the textbook group (n = 30).

Deep learning system assisted detection and localization of lumbar spondylolisthesis.

Explore a new deep learning (DL) object detection algorithm for clinical auxiliary diagnosis of lumbar spondylolisthesis and compare it with doctors' evaluation to verify the effectiveness and feasibility of the DL algorithm in the diagnosis of lumbar spondylolisthesis. Lumbar lateral radiographs of 1,596 patients with lumbar spondylolisthesis from three medical institutions were collected, and senior orthopedic surgeons and radiologists jointly diagnosed and marked them to establish a database. These radiographs were randomly divided into a training set ( = 1,117), a validation set ( = 240), and a test set ( = 239) in a ratio of 0.

Artificial intelligence-aided method to detect uterine fibroids in ultrasound images: a retrospective study.

We explored a new artificial intelligence-assisted method to assist junior ultrasonographers in improving the diagnostic performance of uterine fibroids and further compared it with senior ultrasonographers to confirm the effectiveness and feasibility of the artificial intelligence method. In this retrospective study, we collected a total of 3870 ultrasound images from 667 patients with a mean age of 42.45 years ± 6.

Deep learning-based algorithm improves radiologists' performance in lung cancer bone metastases detection on computed tomography.

Purpose: To develop and assess a deep convolutional neural network (DCNN) model for the automatic detection of bone metastases from lung cancer on computed tomography (CT).

Methods: In this retrospective study, CT scans acquired from a single institution from June 2012 to May 2022 were included. In total, 126 patients were assigned to a training cohort (n = 76), a validation cohort (n = 12), and a testing cohort (n = 38).

Laminin α1 as a target for the treatment of epidural fibrosis by regulating fibrotic mechanisms.

Excessive proliferation and migration of fibroblasts in the lumbar laminectomy area can lead to epidural fibrosis, eventually resulting in failed back surgery syndrome. It has been reported that laminin α1, a significant biofunctional glycoprotein in the extracellular matrix, is involved in several fibrosis‑related diseases, such as pulmonary, liver and keloid fibrosis. However, the underlying mechanism of laminin α1 in epidural fibrosis remains unknown.

Artificial intelligence to detect the femoral intertrochanteric fracture: The arrival of the intelligent-medicine era.

To explore a new artificial intelligence (AI)-aided method to assist the clinical diagnosis of femoral intertrochanteric fracture (FIF), and further compare the performance with human level to confirm the effect and feasibility of the AI algorithm. 700 X-rays of FIF were collected and labeled by two senior orthopedic physicians to set up the database, 643 for the training database and 57 for the test database. A Faster-RCNN algorithm was applied to be trained and detect the FIF on X-rays.

Operative treatment outcomes of anterior sternoclavicular joint dislocation using two experimental methods - an acromioclavicular joint hook plate versus a locking plate: a retrospective study.

Background: We aimed to compare the intraoperative and early postoperative clinical outcomes of using an acromioclavicular joint hook plate (AJHP) versus a locking plate (LP) in the treatment of anterior sternoclavicular joint dislocation.

Methods: Seventeen patients with anterior sternoclavicular joint dislocation were retrospectively analyzed from May 2014 to September 2019. Six patients were surgically treated with an AJHP, and 11 were surgically treated with an LP.

Applications of Mixed Reality Technology in Orthopedics Surgery: A Pilot Study.

The aim of this study is to explore the potential of mixed reality (MR) technology in the visualization of orthopedic surgery. The visualization system with MR technology is widely used in orthopedic surgery. The system is composed of a 3D imaging workstation, a cloud platform, and an MR space station.

Mesenchymal Stem Cell-Derived Exosomes as a Novel Strategy for the Treatment of Intervertebral Disc Degeneration.

Intervertebral disc degeneration (IVDD) has been reported to be the most prevalent contributor to low back pain, posing a significant strain on the healthcare systems on a global scale. Currently, there are no approved therapies available for the prevention of the progressive degeneration of intervertebral disc (IVD); however, emerging regenerative strategies that aim to restore the normal structure of the disc have been fundamentally promising. In the last decade, mesenchymal stem cells (MSCs) have received a significant deal of interest for the treatment of IVDD due to their differentiation potential, immunoregulatory capabilities, and capability to be cultured and regulated in a favorable environment.

Artificial Intelligence to Diagnose Tibial Plateau Fractures: An Intelligent Assistant for Orthopedic Physicians.

Objective: To explore a new artificial intelligence (AI)-aided method to assist the clinical diagnosis of tibial plateau fractures (TPFs) and further measure its validity and feasibility.

Methods: A total of 542 X-rays of TPFs were collected as a reference database. An AI algorithm (RetinaNet) was trained to analyze and detect TPF on the X-rays.

Integration of Artificial Intelligence, Blockchain, and Wearable Technology for Chronic Disease Management: A New Paradigm in Smart Healthcare.

Chronic diseases are a growing concern worldwide, with nearly 25% of adults suffering from one or more chronic health conditions, thus placing a heavy burden on individuals, families, and healthcare systems. With the advent of the "Smart Healthcare" era, a series of cutting-edge technologies has brought new experiences to the management of chronic diseases. Among them, smart wearable technology not only helps people pursue a healthier lifestyle but also provides a continuous flow of healthcare data for disease diagnosis and treatment by actively recording physiological parameters and tracking the metabolic state.

Application of AI and IoT in Clinical Medicine: Summary and Challenges.

The application of artificial intelligence (AI) technology in the medical field has experienced a long history of development. In turn, some long-standing points and challenges in the medical field have also prompted diverse research teams to continue to explore AI in depth. With the development of advanced technologies such as the Internet of Things (IoT), cloud computing, big data, and 5G mobile networks, AI technology has been more widely adopted in the medical field.