BACKGROUND: As the healthcare sector evolves, Artificial Intelligence's (AI's) potential to enhance laboratory medicine is increasingly recognized. However, the adoption rates and attitudes towards AI across European laboratories have not been comprehensively analyzed. This study aims to fill this gap by surveying European laboratory professionals to assess their current use of AI, the digital infrastructure available, and their attitudes towards future implementations. METHODS: We conducted a methodical survey during October 2023, distributed via EFLM mailing lists. The survey explored six key areas: general characteristics, digital equipment, access to health data, data management, AI advancements, and personal perspectives. We analyzed responses to quantify AI integration and identify barriers to its adoption. RESULTS: From 426 initial responses, 195 were considered after excluding incomplete and non-European entries. The findings revealed limited AI engagement, with significant gaps in necessary digital infrastructure and training. Only 25.6 % of laboratories reported ongoing AI projects. Major barriers included inadequate digital tools, restricted access to comprehensive data, and a lack of AI-related skills among personnel. Notably, a substantial interest in AI training was expressed, indicating a demand for educational initiatives. CONCLUSIONS: Despite the recognized potential of AI to revolutionize laboratory medicine by enhancing diagnostic accuracy and efficiency, European laboratories face substantial challenges. This survey highlights a critical need for strategic investments in educational programs and infrastructure improvements to support AI integration in laboratory medicine across Europe. Future efforts should focus on enhancing data accessibility, upgrading technological tools, and expanding AI training and literacy among professionals. In response, our working group plans to develop and make available online training materials to meet this growing educational demand.

• Klíčová slova
• artificial intelligence, digital medicine, new technologies,
• MeSH
• laboratoře MeSH
• lidé MeSH
• průzkumy a dotazníky MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Evropa MeSH

Brain-computer interfaces are used for direct two-way communication between the human brain and the computer. Brain signals contain valuable information about the mental state and brain activity of the examined subject. However, due to their non-stationarity and susceptibility to various types of interference, their processing, analysis and interpretation are challenging. For these reasons, the research in the field of brain-computer interfaces is focused on the implementation of artificial intelligence, especially in five main areas: calibration, noise suppression, communication, mental condition estimation, and motor imagery. The use of algorithms based on artificial intelligence and machine learning has proven to be very promising in these application domains, especially due to their ability to predict and learn from previous experience. Therefore, their implementation within medical technologies can contribute to more accurate information about the mental state of subjects, alleviate the consequences of serious diseases or improve the quality of life of disabled patients.

• Klíčová slova
• Artificial intelligence, Artificial neural networks, Brain–computer interfaces, Fuzzy logic, Machine learning, Nature-inspired optimization techniques,
• MeSH
• algoritmy MeSH
• kvalita života MeSH
• lidé MeSH
• mozek MeSH
• počítače MeSH
• rozhraní mozek-počítač * MeSH
• strojové učení MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH

The current era witnesses a highly dynamic development of Artificial Intelligence (AI) applications, impacting various human activities. Medical imaging techniques are no exception. AI can find application in image acquisition, image processing and augmentation, as well as in the actual interpretation of images. Moreover, within the domain of radiomics, AI can be instrumental in advanced analysis surpassing the capacities of the human eye and experience. While several certified commercial solutions are available, the validation and accumulation of sufficient evidence regarding their positive impact on healthcare is currently constrained. The role of AI presently leans towards being assistive, yet further evolution is anticipated. Risks and disadvantages encompass dependency on computational power, the quality of input data, and their annotation for learning purposes. The transparency of algorithmic functioning is lacking, and issues pertaining to portability may arise. The integration and utilization of AI introduce entirely new ethical and legislative aspects. Predicting the future development of AI in imaging methods is challenging, with a further increase in implementation appearing more probable.

• Klíčová slova
• artificial intelligence (AI) in medicine, imaging methods, radiomics, ethical and legislative aspects, future development of AI,
• MeSH
• diagnostické zobrazování * metody   MeSH
• lidé MeSH
• počítačové zpracování obrazu metody   MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

OBJECTIVE: The aim of this comprehensive paper is to acquaint the readers with evaluation of the retinal images using the arteficial intelligence (AI). Main focus of the paper is diabetic retinophaty (DR) screening. The basic principles of the artificial intelligence and algorithms that are already used in clinical practice or are shortly before approval will be described. METHODOLOGY: Describing the basic characteristics and mechanisms of different approaches to the use of AI and subsequently literary minireview clarifying the current state of knowledge in the area. RESULTS: Modern systems for screening diabetic retinopathy using deep neural networks achieve a sensitivity and specificity of over 80 % in most published studies. The results of specific studies vary depending on the definition of the gold standard, number of images tested and on the evaluated parameters. CONCLUSION: Evaluation of images using AI will speed up and streamline the diagnosis of DR. The use of AI will allow to keep the quality of the eye care at least on the same level despite the raising number of the patients with diabetes.

• Klíčová slova
• Diabetic retinopathy, artificial intelligence, diabetic retinopathy, mass screening, screening,
• MeSH
• algoritmy MeSH
• diabetes mellitus * MeSH
• diabetická retinopatie * diagnóza   MeSH
• inteligence MeSH
• lidé MeSH
• plošný screening MeSH
• umělá inteligence MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Artificial intelligence (AI) has significantly impacted numerous industries, including health care, dentistry, and specifically prosthodontics. This review focuses on AI's role in prosthodontics, detailing its use in diagnosis, design, and manufacturing. AI-driven systems analyze intraoral scans, improve prosthetic planning, and aid in robotic procedures. Emerging technologies, such as generative AI for prosthetic design and AI-driven material innovation, are discussed alongside the ethical and regulatory challenges facing broader adoption. The review highlights AI's potential to transform prosthodontic workflows, facilitating more accurate, efficient, and personalized care, while also pointing to future developments such as real-time monitoring and enhanced collaboration platforms.

• Klíčová slova
• AI, Computer vision, Deep learning, Image analysis, Intraoral scan, Prosthesis,
• MeSH
• design s pomocí počítače MeSH
• lidé MeSH
• stomatologická protetika * metody   MeSH
• umělá inteligence * MeSH
• zubní protéza - design metody   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Artificial intelligence (AI) has made a tremendous impact in the space of healthcare, and proton therapy is not an exception. Proton therapy has witnessed growing popularity in oncology over recent decades, and researchers are increasingly looking to develop AI and machine learning tools to aid in various steps of the treatment planning and delivery processes. This review delves into the emergent role of AI in proton therapy, evaluating its development, advantages, intended clinical contexts, and areas of application. Through the analysis of 76 studies, we aim to underscore the importance of AI applications in advancing proton therapy and to highlight their prospective influence on clinical practices.

• Klíčová slova
• Artificial intelligence, Proton therapy, Review,
• MeSH
• lidé MeSH
• nádory * radioterapie   terapie   MeSH
• plánování radioterapie pomocí počítače metody   MeSH
• protonová terapie * metody   MeSH
• strojové učení MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

The molecular evolution of genomic DNA across diverse plant and animal phyla involved dynamic registrations of sequence modifications to maintain existential homeostasis to increasingly complex patterns of environmental stressors. As an essential corollary, driver effects of positive evolutionary pressure are hypothesized to effect concerted modifications of genomic DNA sequences to meet expanded platforms of regulatory controls for successful implementation of advanced physiological requirements. It is also clearly apparent that preservation of updated registries of advantageous modifications of genomic DNA sequences requires coordinate expansion of convergent cellular proofreading/error correction mechanisms that are encoded by reciprocally modified genomic DNA. Computational expansion of operationally defined DNA memory extends to coordinate modification of coding and previously under-emphasized noncoding regions that now appear to represent essential reservoirs of untapped genetic information amenable to evolutionary driven recruitment into the realm of biologically active domains. Additionally, expansion of DNA memory potential via chemical modification and activation of noncoding sequences is targeted to vertical augmentation and integration of an expanded cadre of transcriptional and epigenetic regulatory factors affecting linear coding of protein amino acid sequences within open reading frames.

• MeSH
• genetika MeSH
• lidé MeSH
• metylace DNA MeSH
• molekulární mimikry MeSH
• umělá inteligence trendy   MeSH
• výpočetní biologie metody   MeSH
• zdraví MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

Due to popular successes (e.g., ChatGPT) Artificial Intelligence (AI) is on everyone's lips today. When advances in biotechnology are combined with advances in AI unprecedented new potential solutions become available. This can help with many global problems and contribute to important Sustainability Development Goals. Current examples include Food Security, Health and Well-being, Clean Water, Clean Energy, Responsible Consumption and Production, Climate Action, Life below Water, or protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss. AI is ubiquitous in the life sciences today. Topics include a wide range from machine learning and Big Data analytics, knowledge discovery and data mining, biomedical ontologies, knowledge-based reasoning, natural language processing, decision support and reasoning under uncertainty, temporal and spatial representation and inference, and methodological aspects of explainable AI (XAI) with applications of biotechnology. In this pre-Editorial paper, we provide an overview of open research issues and challenges for each of the topics addressed in this special issue. Potential authors can directly use this as a guideline for developing their paper.

• Klíčová slova
• Artificial Intelligence, Biotechnology, Deep Learning, Digital Transformation, Machine Learning,
• MeSH
• biotechnologie MeSH
• data mining MeSH
• ekosystém * MeSH
• umělá inteligence * MeSH
• znalostní báze MeSH
• Publikační typ
• úvodní články MeSH

This article presents a summary of recent advances in the development and use of complex systems using artificial intelligence (AI) in neuro-ophthalmology. The aim of the following article is to present the principles of AI and algorithms that are currently being used or are still in the stage of evaluation or validation within the neuro-ophthalmology environment. For the purpose of this text, a literature search was conducted using specific keywords in available scientific databases, cumulatively up to April 2023. The AI systems developed across neuro-ophthalmology mostly achieve high sensitivity, specificity and accuracy. Individual AI systems and algorithms are subsequently selected, simply described and compared in the article. The results of the individual studies differ significantly, depending on the chosen methodology, the set goals, the size of the test, evaluated set, and the evaluated parameters. It has been demonstrated that the evaluation of various diseases will be greatly speeded up with the help of AI and make the diagnosis more efficient in the future, thus showing a high potential to be a useful tool in clinical practice even with a significant increase in the number of patients.

• Klíčová slova
• artificial intelligence, deep learning system, eye movement disorders, neuro-ophthalmology,
• MeSH
• algoritmy MeSH
• lidé MeSH
• oftalmologie * metody   MeSH
• senzitivita a specificita MeSH
• umělá inteligence * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

The article introduces an ambient intelligence system for blind people which besides providing assistance in home environment also helps with various situations and roles in which blind people may find themselves involved. RUDO, the designed system, comprises several modules that mainly support or ensure recognition of approaching people, alerting to other household members' movement in the flat, work on a computer, supervision of (sighted) children, cooperation of a sighted and a blind person (e.g., when studying), control of heating and zonal regulation by a blind person. It has a unified user interface that gives the blind person access to individual functions. The interface for blind people offers assistance with work on a computer, including writing in Braille on a regular keyboard and specialized work in informatics and electronics (e.g., programming). RUDO can complement the standard aids used by blind people at home, it increases their independence and creates conditions that allow them to become fully involved. RUDO also supports blind people sharing a home with sighted people, which contributes to their feeling of security and greater inclusion in society. RUDO has been implemented in a household for two years, which allows an evaluation of its use in practice.

• Klíčová slova
• Key RollOver, Z-Wave, ambient assisted living, artificial neural network, blind people, security, speech synthesis, user interface, work with computer, zone regulation,
• MeSH
• lidé MeSH
• počítače MeSH
• slepota MeSH
• umělá inteligence * MeSH
• uživatelské rozhraní počítače MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH