Результаты поиска

Bronchopulmonary dysplasia predicted at birth by artificial intelligence.

AIM: To develop a fast bedside test for prediction and early targeted intervention of bronchopulmonary dysplasia (BPD) to improve the outcome. METHODS: In a multicentre study of preterm infants with gestational age 24-31 weeks, clinical data present at birth were combined with spectral data of gastric aspirate samples taken at birth and analysed using artificial intelligence. The study was designed to develop an algorithm to predict development of BPD. The BPD definition used was the consensus definition of the US National Institutes of Health: Requirement of supplemental oxygen for at least …

Artificial intelligence and machine learning in spine research.

Artificial intelligence (AI) and machine learning (ML) techniques are revolutionizing several industrial and research fields like computer vision, autonomous driving, natural language processing, and speech recognition. These novel tools are already having a major impact in radiology, diagnostics, and many other fields in which the availability of automated solution may benefit the accuracy and repeatability of the execution of critical tasks. In this narrative review, we first present a brief description of the various techniques that are being developed nowadays, with special focus on those …

[Assistant diagnose for subclinical keratoconus by artificial intelligence].

Objective: To investigate the diagnosis of normal cornea, subclinical keratoconus and keratoconus by artifical intelligence. Methods: Diagnostic study. From January 2016 to January 2019, who admitted to Tianjin Eye Hospital from 18 to 48 years old, with an average of (28.4±8.2) years of myopia patients in 2 018 cases. Two experienced ophthalmologists labeled keratoconus, subclinical keratconus and nomal cornea based on the topography. The data of 80% (1 615 cases) patients were randomly selected as the training set by computer random sampling method, and the data of 20% (403 cases) patients we

Ten Ways Artificial Intelligence Will Transform Primary Care.

Artificial intelligence (AI) is poised as a transformational force in healthcare. This paper presents a current environmental scan, through the eyes of primary care physicians, of the top ten ways AI will impact primary care and its key stakeholders. We discuss ten distinct problem spaces and the most promising AI innovations in each, estimating potential market sizes and the Quadruple Aims that are most likely to be affected. Primary care is where the power, opportunity, and future of AI are most likely to be realized in the broadest and most ambitious scale. We propose how these AI-powered i…

A Novel Artificial Intelligence System for Endotracheal Intubation.

OBJECTIVE: Adequate visualization of the glottic opening is a key factor to successful endotracheal intubation (ETI); however, few objective tools exist to help guide providers' ETI attempts toward the glottic opening in real-time. Machine learning/artificial intelligence has helped to automate the detection of other visual structures but its utility with ETI is unknown. We sought to test the accuracy of various computer algorithms in identifying the glottic opening, creating a tool that could aid successful intubation. METHODS: We collected a convenience sample of providers who each performe…

Artificial intelligence techniques for embryo and oocyte classification.

One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in the capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. This work concentrates the efforts on the possible prediction of the quality of embryos and oocy…

Wayfinding artificial intelligence to detect clinically meaningful spots of retinal diseases: Artificial intelligence to help retina specialists in real world practice.

AIM/BACKGROUND: To aim of this study is to develop an artificial intelligence (AI) that aids in the thought process by providing retinal clinicians with clinically meaningful or abnormal findings rather than just a final diagnosis, i.e., a "wayfinding AI." METHODS: Spectral domain optical coherence tomography B-scan images were classified into 189 normal and 111 diseased eyes. These were automatically segmented using a deep-learning based boundary-layer detection model. During segmentation, the AI model calculates the probability of the boundary surface of the layer for each A-scan. If this p…

Toward the intelligent operating room: Artificial intelligence and computer vision applications in surgery.

The operating room is evolving into an information-rich environment where surgical care is increasingly shaped by integrated digital architectures. The proliferation of minimally invasive and robotic platforms has generated a massive influx of high-resolution video, shifting the field toward real-time computational analysis. Artificial intelligence, particularly computer vision, is moving beyond retrospective analysis to extract structured intelligence from the operative field, redefining how procedures are analyzed and supported. This review focuses on the clinical applications of computer vi…

SFFO-RL-intelligent environmental monitoring: smart sensing networks with artificial intelligence.

Rapid urbanization has led to increasingly severe environmental degradation, necessitating the development of intelligent, adaptable, and explainable monitoring systems for sustainable urban management. Existing modeling frameworks are limited by problems related to sensor noise, data inconsistencies, poor adaptability, and a lack of explanation of how models arrive at their predictions. This study proposes a Satin Firefighter Optimization-Reinforcement Learning (SFFO-RL) model within an Intelligent Environmental Monitoring Framework (IEMF) to enable accurate, interpretable environmental asses

The promise and perils of artificial intelligence in molecular biology.

In this Voices article, six investigators reflect on the growing role of artificial intelligence (AI) in molecular biology research. They discuss AI's potential to accelerate discovery, enhance data analysis, and generate new hypotheses, while also highlighting challenges related to reliability, bias, reproducibility, and the need for human oversight.

Integration of artificial intelligence into pharmacovigilance: A systematic review.

BACKGROUND: Recent advances in machine learning (ML) have sparked the rise of artificial intelligence (AI) in pharmacovigilance (PV). Several studies suggest these technologies could address key PV challenges, including underreporting, manual case processing, and delayed signal detection. PURPOSE: This systematic review aimed to map AI/ML applications across post-marketing PV functions, characterize methodological and geographic trends, and identify evidence gaps in external validation and implementation readiness. METHODS: Following PRISMA 2020 and a Population, Concept, Context (PCC) frame…

The role of artificial intelligence in the diagnosis of pericardial constriction.

PURPOSE OF REVIEW: Constrictive pericarditis is a complex disease whose distinction from clinical mimickers remains challenging yet critically important. Diagnosis frequently requires integration of findings across multiple imaging modalities. Artificial intelligence (AI) applications in cardiac imaging are rapidly evolving and may play an increasingly important role in the diagnosis of constrictive pericarditis. RECENT FINDINGS: Most established evidence supporting AI in diagnosis of constrictive pericarditis involves machine learning and deep learning applied to echocardiography, particular…

[Expert consensus on the application of artificial intelligence in stomatology].

In recent years, artificial intelligence (AI) has rapidly advanced in the field of oral medicine, with applications extending across disease screening, diagnosis assistance, treatment planning, prognosis prediction, and dental education. Powered by deep learning and multimodal analytics, AI can efficiently integrate data from cone beam CT, intraoral scans, and electronic health records, enhancing precision and efficiency in managing dental caries, endodontic and periodontal diseases, oral mucosal lesions, and maxillofacial trauma. AI also contributes to omics research, biomaterial development,…

Artificial Intelligence in the Discovery of Bioactive Natural Products.

Artificial intelligence (AI) is transforming natural products discovery by integrating genome mining, metabolomics, bioactivity prediction, and virtual screening into unified computational ecosystems. This review provides a comprehensive overview of AIdriven approaches for the discovery of bioactive natural products, covering AI-ready databases, machine learning tools for biosynthetic gene cluster (BGC) prediction, metabolomics platforms, NMR and MS spectral interpretation, and translational development. The convergence of AI with multi-omics technologies, synthetic biology, and automated expe…

Применение искусственного интеллекта в перипостетической суставной инфекции.

Перипростетическая суставная инфекция (ПСО) представляет собой one Из наиболее разрушительных осложнений, вызванных общей совместной артропластикой, часто требующих дополнительных операций и антимикробной терапии, и потенциально ведущих к инвалидности. Это значительно увеличивает нагрузку как на пациентов, так и на систему здравоохранения. С учетом значительных страданий, причиняемых ПСО, его профилактика и лечение уже давно являются ключевыми факторами, вызывающими озабоченность. Вместе с тем сохраняются проблемы, связанные с точной оценкой индивидуального риска, предотвращением инфекции, сов

Совпадение в аннотации оригинала
Periprosthetic joint infection (PJI) represents one of the most devastating complications following total joint arthroplasty, often necessit … improving diagnostic methods, and enhancing treatment outcomes. The development and application of artificial intelligence (AI) technologies have introduced new, more efficient possibilities for the management of many diseases. In this article, we review the applications of AI in the prevention, diagnosis, and treatment of PJI, and explore how AI methodologies might ach …

A Scoping Review of Artificial Intelligence in Ocular Oncology.

Objective: To provide a comprehensive literature review of original work on artificial intelligence in ocular oncology. Methods: Scoping review of PubMed-indexed original articles (n = 94) on the use of artificial intelligence in ocular oncology, retrieved during the month of February 2026 and independently screened by two ocular oncologists. Results: Most of the literature on artificial intelligence (AI) in ocular oncology focuses on uveal melanoma and its differentials (n = 39, 41%), followed by retinoblastoma (n = 14, 15%) and orbital tumors (n = 12, 13%). The purpose of using the AI models…

Artificial intelligence for sepsis management in the emergency department.

Sepsis a major cause of emergency department (ED) presentations, with over 850,000 cases annually in the United States alone. Despite decades of research and numerous clinical trials, sepsis management still relies on the basic principles of infection control and organ support, with no sepsis-specific therapies proving universally effective. Recent advances in artificial intelligence (AI) offer new opportunities to address this challenge by supporting clinicians in early detection, optimizing diagnostic work-ups, and improving treatment decisions. This narrative review highlights the potential…

Artificial Intelligence for the Automated Measurement of Hiatal Dimensions.

INTRODUCTION AND HYPOTHESIS: The levator hiatus is an important determinant of pelvic organ prolapse and prolapse recurrence after surgery. Manufacturers are now offering automatic determination of hiatal dimensions. METHODS: This was an observational study using data sets of 437 women attending a urogynaecological unit in 2024 and 2025. All had 4D pelvic floor ultrasound using a Voluson E 22 system with SonoPelvic™ software. Data sets obtained on Valsalva were used for automated measurements. Manual measurements were performed later on stored data sets blinded against all other data. For sta

The use of artificial intelligence in advancing health for seafarers.

The maritime industry is undergoing rapid digital transformation, with artificial intelligence (AI) increasingly influencing the delivery and governance of health services for seafarers. This short communication explores the potential role of AI in addressing persistent occupational health challenges faced by maritime workers, including limited access to healthcare, fatigue, and mental health risks. AI-enabled applications in telemedicine, clinical decision support, and predictive analytics offer opportunities to enhance prevention, early detection, and continuity of care at sea. However, effe…