ChatGPT is a generative language model tool launched by OpenAI on November 30, 2022, enabling the public to converse with machine broad range of topics. In January 2023, reached over 100 million users, making it fastest-growing consumer application date. This interview part 2 larger ChatGPT. It provides snapshot current capabilities and illustrates vast potential for medical education, research, practice but also hints at problems limitations. this conversation Gunther Eysenbach, founder publisher JMIR Publications, generated some ideas how use chatbots in education. illustrated its generate virtual patient simulation quizzes students; critiqued simulated doctor-patient communication attempts summarize research article (which turned out be fabricated); commented methods detect machine-generated text ensure academic integrity; curriculum health professionals learn about artificial intelligence (AI); helped draft call papers new theme issue Medical Education The highlighted importance proper “prompting.” Although generator does make occasional mistakes, admits these when challenged. well-known disturbing tendency large models hallucinate became evident fabricated references. glimpse into limitations future AI-supported Due impact technology launching e-collection issue. initial was entirely ChatGPT, will edited human guest editors

Artificial Intelligence (AI) plays an increasingly important role in improving HCI and user experience. Yet many challenges persist designing innovating valuable human-AI interactions. For example, AI systems can make unpredictable errors, these errors damage UX even lead to undesired societal impact. However, routinely grapples with complex technologies mitigates their unintended consequences. What makes different? interaction appear particularly difficult design? This paper investigates questions. We synthesize prior research, our own design research experience, observations when teaching interaction. identify two sources of AI's distinctive challenges: 1) uncertainty surrounding capabilities, 2) output complexity, spanning from simple adaptive complex. four levels systems. On each level, designers encounter a different subset the challenges. demonstrate how findings reveal new insights for designers, researchers, tool makers productively addressing going forward.

In recent years, artificial intelligence (AI) has become an emerging trend in different fields: science, business, medicine, automotive and education. AI also reached marketing. The aim of the paper is to research how deeply applied marketing what implications there are for practitioners. Authors stated two questions - which areas used delivers managers. To answer those questions, authors conducted on secondary data with examples purpose. analysis gathered shows that widely introduced into field, though applications at operational level. This may be effect careful implementation new technology, still level experimenting it. uncertainty outcome affect caution putting these innovations practice as well. Gathered proved influences all aspects mix impacting both consumer value delivery well organization management. especially ideas about implementing marketing, designing incorporate skills team required by technology.

Artificial intelligence is likely to perform several roles currently performed by humans, and the adoption of artificial intelligence-based medicine in gastroenterology practice expected near future. Medical image-based diagnoses, such as pathology, radiology, endoscopy, are be first medical field affected intelligence. A convolutional neural network, a kind deep-learning method with multilayer perceptrons designed use minimal preprocessing, was recently reported being highly beneficial including esophagogastroduodenoscopy, colonoscopy, capsule endoscopy. network-based diagnostic program challenged recognize anatomical locations esophagogastroduodenoscopy images, <i>Helicobacter pylori</i> infection, gastric cancer for esophagogastroduodenoscopy; detect classify colorectal polyps; celiac disease hookworm; small intestine motility characterization endoscopy images. help endoscopists provide more accurate diagnosis automatically detecting classifying lesions; therefore, it essential that focus on this novel technology. In review, we describe effects special automatic diagnosis, based endoscopic findings.

Artificial Intelligence (AI) plays a pivotal role in drug discovery. In particular artificial neural networks such as deep or recurrent drive this area. Numerous applications property activity predictions like physicochemical and ADMET properties have recently appeared underpin the strength of technology quantitative structure-property relationships (QSPR) structure-activity (QSAR). intelligence de novo design drives generation meaningful new biologically active molecules towards desired properties. Several examples establish field. Combination with synthesis planning ease is feasible more automated discovery by computers expected near future.

Despite the great media attention for artificial intelligence (AI), many health care professionals term and functioning of AI remain a "black box," leading to exaggerated expectations on one hand unfounded fears other. In this review, we provide conceptual classification brief summary technical fundamentals AI. Possible applications are discussed basis typical work flow in medical imaging, grouped by planning, scanning, interpretation, reporting. The main limitations current techniques, such as issues with interpretability or need large amounts annotated data, briefly addressed. Finally, highlight possible impact nuclear medicine profession, associated challenges and, last but not least, opportunities.

Smart manufacturing (SM) is a term generally applied to the improvement in operations through integration of systems, linking physical and cyber capabilities, taking advantage information including leveraging big data evolution. SM adoption has been occurring unevenly across industries, thus there an opportunity look other industries determine solution roadmap paths for such as biochemistry or biology. The evolution affords managing significantly larger amounts acting on it with analytics improved diagnostics prognostics. approaches can be defined terms dimensions understand their requirements technology gaps. semiconductor industry by improving existing capabilities fault detection, supporting new predictive maintenance. For most these capabilities: (1) quality important factor delivering high solutions; (2) incorporating subject matter expertise often required realizing effective on-line solutions. In future, environment smart concepts digital twin will further enable analytics; however, anticipated that need design remain.

Artificial intelligence (AI), which includes machine learning and deep has been introduced to nursing care in recent years. The present study reviews the following topics: concepts of AI, learning, learning; examples AI-based research; necessity education on AI schools; areas where is useful. refers an intelligent system consisting not a human, but machine. Machine computers’ ability learn without being explicitly programmed. Deep subset that uses artificial neural networks multiple hidden layers. It suggested educational curriculum should include big data, concept algorithms models model coding practice. standard be organized by society. An example area useful prenatal interventions based pregnant women’s records prediction risk delivery according age. Nurses able cope with rapidly developing environment influenced understand how apply their field. time for Korean nurses take steps become familiar research, education,

Abstract The study presents the results regarding attitudes of students from humanities and technical specializations in Timișoara towards emergence development artificial intelligence (AI). emphasis was on most likely consequences future, especially negative that its would entail. method used for data collection sociological survey information gathering tool questionnaire. It applied to a total 929 people, ensuring sample representativity margin ± 3%. analysis reveals participants predict due AI, interpersonal relationships will be negatively affected, there fewer jobs, economic crises emerge, it make intelligent weapons, increase military conflicts, take control humanity and, last but not least, destroy mankind. revealed differences responses depending type specialization (humanities or technical) gender respondents.

Background Artificial intelligence (AI) is set to transform the health system, yet little research date has explored its influence on nurses—the largest group of professionals. Furthermore, there been discussion how AI will experience person-centered compassionate care for patients, families, and caregivers. Objective This review aims summarize extant literature emerging trends in technologies powered by their implications following domains nursing: administration, clinical practice, policy, research. summarizes findings from 3 questions, examining these might roles functions nurses nursing over next 10 years beyond. Methods Using an established scoping methodology, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database Systematic Reviews, Central, Education Resources Information Center, Scopus, Web Science, ProQuest databases were searched. In addition electronic database searches, a targeted website search was performed access relevant gray literature. Abstracts full-text studies independently screened 2 reviewers using prespecified inclusion exclusion criteria. Included articles focused digital that incorporate AI. Data charted structured forms narratively summarized. Results A total 131 retrieved questions focus this manuscript (118 sources 13 websites). Emerging discussed included predictive analytics, smart homes, virtual assistants, robots. The results indicated already begun roles, workflows, nurse-patient relationship. general, robots are not viewed as replacements nurses. There consensus may have potential enhance practice. Consequently, must proactively define be preserved age Conclusions Nurses shared responsibility decisions related integration into system ensure change introduced way ethical aligns with core values such care. advocate patient involvement all aspects design, implementation, evaluation technologies. International Registered Report Identifier (IRRID) RR2-10.2196/17490

Background The importance of infectious disease epidemic forecasting and prediction research is underscored by decades communicable outbreaks, including COVID-19. Unlike other fields medical research, such as clinical trials systematic reviews, no reporting guidelines exist for despite their utility. We therefore developed the EPIFORGE checklist, a guideline standardized research. Methods findings this checklist using best-practice process development guidelines, involving Delphi broad consultation with an international panel modelers model end users. objectives these are to improve consistency, reproducibility, comparability, quality reporting. not designed advise scientists on how perform but rather serve standard critical methodological details studies. Conclusions These have been submitted EQUATOR network, in addition hosting dedicated webpages facilitate feedback journal endorsement.

This article begins by asking: 'Why are robots not becoming domestic products?' In addressing this question the author borrows from science of ecology and biological concepts evolution domestication to make an analogy between shift habitats that occurs when organism successfully goes through process artificial selection (from natural domestic). addition, paper explores transition emerging technology makes coming out laboratory a suitable product for use, concluding majority proposed essentially maladapted everyday life. The then shifts focus onto design research, primarily speculative design, ask, 'how could become uses variety projects describe how alternative approaches can provide new perspectives on technological research development.

Introduction Artificial intelligence (AI), the simulation of human processes by machines, is being increasingly leveraged to facilitate clinical decision-making. AI-based decision support (CDS) tools can improve quality care and appropriate use healthcare resources, decrease provider burnout. Understanding determinants implementing CDS in delivery vital reap benefits these tools. The objective this scoping review map synthesise (barriers facilitators) healthcare. Methods analysis This will follow Joanna Briggs Institute methodology Preferred Reporting Items for Systematic reviews Meta-Analysis extension Scoping Reviews checklist. search terms be tailored each database, which includes MEDLINE, Embase, CINAHL, APA PsycINFO Cochrane Library. Grey literature references included studies also searched. include published from database inception until 10 May 2022. We not limit searches study design or language. Studies that either report describe implementation practice or/and settings included. identified described synthesising themes using Theoretical Domains Framework. outcome variables measured mapped measures effectiveness summarised descriptive statistics. Ethics dissemination approval required because all data have been previously published. findings a peer-reviewed journal presented at academic conferences. Importantly, widely decision-makers, health system administrators, providers, patients family/caregivers as part an treatment coronary artery disease.

Abstract This article investigates cybersecurity (and risk) in the context of ‘technological singularity’ from artificial intelligence. The investigation constructs multiple risk forecasts that are synthesised a new framework for counteracting risks intelligence (AI) itself. In other words, research this is not just concerned with securing system, but also analysing how system responds when (internal and external) failure(s) compromise(s) occur. an important methodological principle because all systems can be secured, totally feasible. Thus, we need to construct algorithms will enable continue operating even parts have been compromised. Furthermore, emerging cyber-risks integration AI cybersecurity. Based on forecasts, concentrated creating synergies between existing literature, data sources identified survey, forecasts. used increase feasibility overall development novel methodologies uses defend cyber risks. methodology focused addressing attacks, as well forecast value defence prevention rogue devices acting independently.

When cognitive computing enabled smart computers are growing in our daily lives, there not many studies that explain how people interact and utilize these solutions, the impact of machines to people’s performance do things. In this paper, a theoretical framework for boosting using assistants (CAs) was developed explained data analysis from 15 interviews. The results show interaction with CAs enhance their levels cognition intelligence help them capabilities. Enhanced capabilities performance.

Key words: copyright, work, artificial intelligence, computer program In the article, problemsof legislation of Ukraine regarding issues copyright on works created due to artificialintelligence were analyzed. Particularly, who is owner ofworks intelligence. On one hand, it could be a developer ofa program, from other client or an employer. Because,it happen that there situation when robots something newand original, e.g., how happened with project “New Rembrandt”. this case,computers unique portrait Rembrandt. And here question, where isin original and intellectual developers these computers andprograms. contrast, without people developedspecial machines, programs, computers. The article’s author proposes addinto Ukrainian following norm: createddue intelligence should natural person uses intelligencefor purposes within official relationship basis contract. caseof automatic generation such work by copyrightshould developer.Also, another question arises, particularly, will responsible for damagecaused As example, solution issue Resolution2015/2103 (INL) was given, mentioned human agent responsiblefor caused damage. Because, not always damage.Also, justice practice foreign countries explored. Theways overcoming problems in proposed.Such as changing our giving exact explanation ownerof which cases personcould become copyright. However, probably, shouldbe resolved at international level globalization.

Purpose The purpose of this paper is to raise awareness on the need for a more comprehensive approach interdependence between artificial intelligence (AI) and environmental sustainability. It provides an overview existing sustainable AI policy initiatives at national regional level. More precisely, it discusses whether European Union (EU) policies are suitable era or new regulations needed in field. Finally, assesses cross-fertilisation opportunities EU non-EU countries. Design/methodology/approach This study based qualitative analysis applications sustainability AI. Emphasis laid latter, “sustainable by design” proposed, which essence prerequisite transparent, responsible human-centred systems. primarily focuses Findings majority studies focus how use protect environment with very little attention paid design On other hand, EU’s towards closest promoting Several ways have been identified actions can be translated beyond its borders. Research limitations/implications One largest limitations moderate scope. confined as such limited assessment global measures interplay Consequently, did not provide in-depth worldwide that could help better picture possible cooperation areas common grounds. Another limitation aspects accords economic social pillars Social implications With less than 10 years go before reaching development goal deadline, stakeholders understand what being done terms Moreover, given technology still early phase, inspire technologies. Originality/value All strategies published 1 June 2021 were analysed identify extent they prioritise Furthermore, authors also looked aims address from perspective.

Data-driven science and its corollaries in machine learning the wider field of artificial intelligence have potential to drive important changes medicine. However, medicine is not a like any other: It deeply tightly bound with large wide network legal, ethical, regulatory, economical, societal dependencies. As consequence, scientific technological progresses handling information further processing cross-linking for decision support predictive systems must be accompanied by parallel global environment, numerous stakeholders, including citizen society. What can seen at first glance as barrier mechanism slowing down progression data must, however, considered an asset. Only adoption transform big into effective breakthroughs health This requires society, scientists citizens, progress together.

Certainty and uncertainty are fundamental to science communication. Hedges have widely been used as proxies for uncertainty. However, certainty is a complex construct, with authors expressing not only the degree but type aspects of in order give reader certain impression what known. Here, we introduce new study that models both level scientific findings. Using dataset 2167 annotated findings, demonstrate hedges alone account partial explanation certainty. We show overall individual can be predicted pre-trained language models, providing more complete picture author's intended Downstream analyses on 431K findings from news abstracts modeling sentence-level aspect-level meaningful areas like Both model datasets this paper released at https://blablablab.si.umich.edu/projects/certainty/.

Digital Twin technology has been rising in popularity thanks to the of machine learning last decade. As life expectancy people around world is increasing, so focus on physical activity remain healthy especially current times where are staying sedentary while quarantine. This article aims provide a survey field focusing and coaching techniques as they have not explored yet. We also define what Coaching categorize work done far terms objective activity. list common characteristics found articles reviewed concepts such interactivity, privacy security detail future perspectives multimodal interaction standardization, name few, that can guide researchers if choose this field. Finally, we diagram for Ecosystem showing between relevant entities information flow well an idealization ideal team sports’ athlete tracking.

Every day more and companies rely on artificial intelligence, from small startups to large companies, among which stand out not only the IT giants Google, Microsoft, Facebook, IBM, but even those that seemingly far this topic - for example, General Motors Boeing created a joint laboratory AI research. It becomes obvious technology is real mainstream of our time. The article examines global market intelligence systems technologies. authors described peculiarities formation main trends segments in its development. goal research identify dynamics, features methodology system analysis, dialectical method scientific cognition, methods historical, logical comparative analysis are used. concept has been systematized, dynamics technologies have revealed, as well regional context. relationship between sharp jump performance information processing algorithms, became possible due fast computer based GPUs, an avalanche-like data growth emergence almost unlimited possibilities storage access, detected. shown phase inflated expectations with high enough level risk investors. development identified. These include deep learning technologies, convergence other such analytics, ERP, Internet Things, blockchain, quantum computing, greatest impact, cognitive systems, creation computer. business leaders consider fundamental absolutely necessary future opportunities. proven rapid just another technological innovation, platform Fourth Industrial Revolution, associated hopes accelerating economic world economy, increasing competitiveness countries companies.

Objective: Artificial intelligence (AI) is the new buzzword that trendy in multiple branches of dentistry. The aim this study was to assess perceptions and utilization AI among dental professionals Saudi Arabia. Methods: This a cross-sectional investigating 389 students dentists from 22 cities Arabia using validated self-reported questionnaire. Results: A total 49.4% participants reported knowing what is; 44.5% having basic knowledge principles, 42.2% know uses most common information source social media (66.07%). Out 17 attitude items, 16 were scored above midpoint. 75.0% agreed or strongly will lead major advances In contrast, 49.1% could replace future. There no significant differences by gender region, but interns had significantly higher scores than did dentists. widespread desire take professional courses use (69.7%), some used applications (25.4%) taken an course (18.5%–20.3%). barriers non-availability (73%) lack time (68.9%). Conclusion: Dental have moderate awareness levels high rates good attitudes about However, practice limited. Incorporating curricula crucial due worldwide digital transformation.

Issues, arising in the field of intellectual property rights connection with development artificial intelligence systems and their impact on legal relations economy culture modern society, have been considered. Aspects mutual policies for innovation creativity examined. Questions copyright ownership interaction man, collective or raised proposed. Issues related to as an object The position author personality objects created by autonomous has presented, which is expressed answers questions project World Intellectual Property Organization wide discussion interested parties, planned 2020 at headquarters Geneva. main conceptual principle issues grant right a dressed subject – person collective, developer fixation latter sub-subject instrument subject. Traditional categories also considered, such patentability inventive level possible generation these intelligence. data, its generation, fabrications regarding data Harmonization international alleviate technological gap between countries context

The ability to accurately predict the mechanical properties of metals is essential for their correct use in design structures and components. This even more important presence materials, such as metal cast alloys, whose can vary significantly relation constituent elements, microstructures, process parameters or treatments. study shows how a machine learning approach, based on pattern recognition analysis experimental data, able offer acceptable precision predictions with respect main metals, case ductile iron compact graphite iron. metallographic properties, graphite, ferrite perlite content, extrapolated through macro indicators from micrographs by image analysis, are used inputs algorithms, while yield strength, ultimate strain Young’s modulus, derived output. In particular, 3 different algorithms trained starting dataset 20–30 data each material results high accuracy, often better than other predictive techniques. Concerns regarding applicability these techniques product/process quality control also discussed.

A deep learning-based convolutional artificial neural networks structured a new image classification method approach was implemented in the study. Sample application carried out with Diabetic Retinopathy disease. Obtaining information about blood vessels and any abnormal patterns from rest of phonoscopic assessing degree retinopathy is problem itself. To solve this developed methodology algorithmic structure presented An called care model used study different classical CNN structure. The based on idea that best solution will be taken data obtained by rescale available according to total number pixels before average pool created then processes continue. In approach, all multiplied elements epoch time eight tensors. purposed include VGG19 mathematical presented. Pre-trained dataset kaggle keras for implementation case provide train accuracy 87%, test 88%, precision 93% recall 83%.