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Background: Accurate, timely fracture detection remains challenging, especially in low-resource settings with limited radiology expertise. Open-source deep learning models offer accessible computer vision tools for fracture detection, but their real-world reli…
crossref
Abdullah Jalal, Fatimah Jalal, Elizabeth Theirl, Umar Hashim 等
2026-07-29T06:12:24Z
置信度 0.70
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The development and deployment of medical artificial intelligence (AI) systems are limited by two persistent gaps: clinician knowledge is often introduced late in development as labels or annotations, and deployed systems often provide outputs that are difficu…
crossref
Wenxin Xue, Rong Lin, Hongliu Du, Prateek Sharma 等
2026-08-04T13:51:27Z
置信度 0.70
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Patients' waiting time is a major issue in the Canadian healthcare system. The planning for resource allocation impacts patients' waiting time in medicare settings. This research focuses on the reduction of patients' waiting time by providing better planning f…
crossref
Tasquia Mizan, Sharareh Taghipour
2022-10-27T19:26:57Z
置信度 0.70
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crossref
Salvatore D’Antonio, Federica Uccello
2025-01-22T01:53:25Z
置信度 0.70
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crossref
Hesham Elhalawani, Raymond Mak
2021-04-21T13:56:35Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2006-10-27T16:12:37Z
置信度 0.70
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crossref
2011-07-24T18:35:49Z
置信度 0.70
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crossref
2010-02-19T09:17:40Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-09-11T23:30:03Z
置信度 0.70
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crossref
2003-09-22T15:25:23Z
置信度 0.70
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This chapter looks at the path from single-purpose AIs to artificial general intelligence (AGI) defined as an AI that is as flexible as human intelligence in its ability to work across different domains and to adapt to new challenges. AI’s capacity to understa…
crossref
Tony Prescott
2024-05-13T16:41:42Z
置信度 0.70
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crossref
2007-12-19T16:27:00Z
置信度 0.70
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crossref
2003-09-11T23:30:03Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-09-11T23:30:03Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T08:02:52Z
置信度 0.70
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crossref
2003-03-14T08:02:52Z
置信度 0.70
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crossref
2010-07-24T06:47:33Z
置信度 0.70
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crossref
2003-03-14T08:02:52Z
置信度 0.70
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crossref
2003-03-14T08:02:52Z
置信度 0.70
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Artificial intelligence (AI) is a region of computer techniques that deals with the design of intelligent machines that respond like humans. It has the skill to operate as a machine and simulate various human intelligent algorithms according to the user’s choi…
crossref
T.D. Raheni, P. Thirumoorthi
2020-11-02T14:18:07Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-09-11T23:30:03Z
置信度 0.70
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crossref
2004-08-27T14:24:01Z
置信度 0.70
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crossref
2003-09-16T21:11:43Z
置信度 0.70
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crossref
2011-01-22T04:24:13Z
置信度 0.70
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crossref
2004-02-26T13:25:52Z
置信度 0.70
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crossref
2002-10-16T09:46:38Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T08:02:52Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T08:02:52Z
置信度 0.70
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crossref
2002-12-29T21:45:55Z
置信度 0.70
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crossref
2004-02-26T13:25:52Z
置信度 0.70
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crossref
2003-03-14T13:02:52Z
置信度 0.70
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crossref
2003-03-14T08:02:52Z
置信度 0.70
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crossref
2004-02-13T05:06:52Z
置信度 0.70
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The international human right to health states that people have claims to access goods, services, and infrastructure that protects an adequate standard of health. The current and forthcoming advances in artificial intelligence (AI), which significantly improve…
europepmc
2026
置信度 0.80
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Large language models (LLMs) show great potential for clinical decision-making, yet most applications remain narrow, task-specific chat tools rather than systems integrated into clinical workflows 1,2 . However, building physician copilots will require models …
europepmc
2026
置信度 0.80
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Randomised controlled trials (RCTs) testing artificial intelligence (AI) approaches in health care (AI-RCTs) mostly use measures of processes rather than measures of health outcomes. Measures of processes refer to indicators that assess the performance of a to…
europepmc
2026
置信度 0.80
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Advances in large language models (LLMs) have accelerated medical benchmarking, yet most evaluation of LLMs still relies on exam-style question answering or curated vignettes that test knowledge rather than performance in clinical workflows.1 Such benchmarks o…
europepmc
2026
置信度 0.80
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This descriptive and correlational study examined the relationship between completion of an Informatics Techniques in Nursing course and nursing students' readiness to use medical artificial intelligence, as well as the mediating role of informatics competence…
europepmc
2026
置信度 0.80
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This study aimed to translate and culturally adapt the Medical Artificial Intelligence Readiness Scale for Medical Students into Korean and to examine its validity and reliability among nursing students. The scale designed in this methodological and cross-sect…
europepmc
2026
置信度 0.80
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Artificial intelligence offers students more personalised and adaptive learning, which encourages educators to better understand students' learning processes. This study aims to determine the readiness levels of medical faculty students in medical artificial i…
europepmc
2026
置信度 0.80
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Data sharing is not applicable to this article as no data sets were generated or analysed during the current study.
europepmc
2026
置信度 0.80
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Importance Artificial intelligence (AI) is increasingly used in clinical care, but widespread adoption requires patient trust. Trust may be enhanced through systemic governance mechanisms or frontline clinicians providing a human in the loop for AI oversight. …
europepmc
2026
置信度 0.80
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Introduction Artificial intelligence (AI) is rapidly transforming healthcare systems and clinical practice, increasing the need to prepare future physicians to work effectively with AI technologies in clinical contexts. Despite growing interest in integrating …
europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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europepmc
2026
置信度 0.80
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This study examines the impact of medical artificial intelligence (AI) on physician workload and the quality of patient care. A meta-analysis of empirical studies found that AI significantly reduces physician workload and diagnostic time by automating repetiti…
europepmc
2026
置信度 0.80
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In recent years, artificial intelligence in medicine has evolved from single recognition tasks toward structural understanding, spatial reasoning, and clinical interpretability. High-quality anatomical data have become a key factor in further development. Driv…
europepmc
2026
置信度 0.80
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The rapid expansion of the medical artificial intelligence (AI) literature has outpaced our ability to judge how far published models have progressed towards clinical use. We investigated whether the translational maturity of a study can be estimated automatic…
europepmc
2026
置信度 0.80
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Explainability has increasingly become a core requirement for intelligent medical devices. Current medical artificial intelligence (AI) technologies suffer from the 'interpretability gap' despite tremendous efforts for enhancing explainability. Here we propose…
europepmc
2026
置信度 0.80
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The increasing use of AI in healthcare has sparked debates about responsibility and accountability for AI-related errors. The difficulty in attributing moral responsibility for undesirable outcomes caused by increasingly autonomous (often opaque) AI systems ha…
europepmc
2026
置信度 0.80
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BACKGROUND: This study aims to analyse the correlation between surgical unit nurses’ artificial intelligence literacy levels and their medical artificial intelligence readiness. METHOD: The study was descriptive, exploratory, and cross-sectional, and was condu…
europepmc
2025
置信度 0.80
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Globally, millions of individuals suffer from infectious diseases, which are major public health concerns caused by bacteria, fungi, viruses, or parasites. These diseases can be transmitted directly or indirectly from person to person, potentially leading to a…
europepmc
2026
置信度 0.80
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Objectives To conduct a nationwide survey among professionals working in oncology departments in China to investigate their attitudes, perceptions, and experiences regarding medical artificial intelligence (AI), and to explore and compare the factors influenci…
europepmc
2026
置信度 0.80
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Medical artificial intelligence (AI) offers transformative potential for earlier disease detection, equitable access, and safer, more consistent care. However, its advancement depends on large-scale, multimodal, and longitudinal clinical data, which are highly…
europepmc
2026
置信度 0.80
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As artificial intelligence (AI) becomes increasingly central to modern healthcare, medical education must move beyond passive knowledge transfer and adopt a system-wide approach to convergence training. This narrative review shares a 5-year case study from Seo…
europepmc
Tae In Park, Jong-Mo Seo, Hyung-Jin Yoon, Kyu Eun Lee
2025
置信度 0.80
Convergence (economics)Modular designCurriculumKey (lock)Scalability
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Artificial intelligence (AI) systems are now prevalent in our daily lives and hold promise for transforming high-stakes fields such as healthcare. Medical AI systems are showing significant potential to support diagnostics and treatment recommendations. As the…
europepmc
Chanwoo Kim, Soham U. Gadgil, Su-In Lee
2025-09-10T10:29:30Z
置信度 0.80
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Artificial intelligence (AI) has the capacity to improve patient care through increasing clinical decision-making accuracy and reducing administrative burdens for clinicians. However, AI poses challenges in medical ethics due to its opaque nature, potential fo…
europepmc
2025
置信度 0.80
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europepmc
2025
置信度 0.80
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Artificial intelligence (AI) increasingly influences clinical decision-making, yet its recommendations may diverge from standard care. Although malpractice concerns are thought to discourage physicians from following AI advice, experimental evidence from the U…
europepmc
2026
置信度 0.80
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The rapid expansion of artificial intelligence (AI) in healthcare has led to increasing adoption of AI-based software as a medical device (SaMD). This paper reviews the current regulatory and approval framework for AI-based SaMD in Japan and discusses emerging…
europepmc
2026
置信度 0.80
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Artificial intelligence (AI) has experienced rapid growth in recent years with the advent of high-profile tools such as ChatGPT. However, its roots extend deep into the twentieth century. This article retraces the origins of AI and its major developments, show…
europepmc
2026
置信度 0.80
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Considerations around model retraining are standard practice in industry and non-healthcare sectors; however, this is much less well explored in medical artificial intelligence (AI). The problem is not only that models often fail to generalise, but that academ…
europepmc
2026
置信度 0.80
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This systematic review assessed the scope, reporting quality, and methodological risk of bias of health economic evaluations (HEEs) of medical artificial intelligence (AI) technologies, alongside the technological maturity of the AI systems assessed.
pubmed
Godoy Junior CA, Boverhof BJ, Rutten-van Mölken MPMH, Bijleveld L 等
2026
置信度 0.82
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pubmed
Matsubara S
2025-12-10T06:23:41Z
置信度 0.82
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Aim This study aims to evaluate the mediating role of artificial intelligence (AI) anxiety in the effect of nurses' attitudes toward health technologies on their readiness for medical artificial intelligence (MAI). Methods A cross-sectional design was used. Th…
europepmc
2026
置信度 0.80
-
europepmc
2025
置信度 0.80
-
pubmed
Islam N, Rahman Osman A
2026
置信度 0.82
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Medical artificial intelligence (AI) is currently undergoing rapid development, with its technical framework evolving from symbolic reasoning to a new paradigm driven by deep learning and large language models. This article reviews the progression of AI techno…
europepmc
2026
置信度 0.80
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Artificial intelligence (AI) technologies are already having significant impacts in healthcare 1 . For example, AI-guided imaging has shown promise in the management of vascular diseases, including carotid, aortic, and peripheral artery disease, which collecti…
europepmc
2025
置信度 0.80
-
Background Despite the increasing use of machine learning (ML) in clinical research, the early stages of data preparation, especially for structured clinical data, often receive limited methodological scrutiny. These datasets typically contain missing values, …
europepmc
2026
置信度 0.80
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The rapid advancement of artificial intelligence is profoundly reshaping clinical practice and transforming the doctor-patient relationship from a traditional physician-patient dyad to a composite structure of "physician + AI-patient". While this structural sh…
europepmc
2025
置信度 0.80
-
Artificial intelligence (AI) has advantages such as improving work performance, enhancing time efficiency, and reducing work costs, and has been widely applied in various industries, including healthcare. A comprehensive evaluation of medical AI is significant…
europepmc
2025
置信度 0.80
-
Aim The aim of this study is to examine the preparedness levels of nursing students for Medical Artificial Intelligence and Artificial Intelligence Anxiety. Design This is a descriptive mixed-method study. Methods The medical artificial intelligence readiness …
europepmc
Rukiye Burucu, Hilal Türkben Polat
2025
置信度 0.80
-
Unlabelled Rigorous evaluation of generalist medical artificial intelligence (GMAI) is imperative to ensure their utility and safety before implementation in health care. Current evaluation strategies rely heavily on benchmarks, which can suffer from issues wi…
europepmc
2025
置信度 0.80
-
Aim This study examined the relationships among nursing students' readiness for medical AI, AI literacy and their attitudes toward AI within digitalization in healthcare. Background The rapid integration of AI into healthcare highlights the need to assess futu…
europepmc
2025
置信度 0.80
-
The landscape of medical artificial intelligence (AI) is experiencing unprecedented momentum. Since January, 2023, the number of publications on this subject has remarkably increased, with each new use case for large language models (LLMs) generating cascading…
europepmc
2025
置信度 0.80
-
Amid the global wave of digital economy, China's medical artificial intelligence applications are rapidly advancing through technological innovation and policy support, while facing multifaceted evaluation and regulatory challenges. The dynamic algorithm evolu…
europepmc
2025
置信度 0.80
-
The notion of medical digital twins is gaining popularity both within the scientific community and among the general public; however, much of the recent enthusiasm has occurred in the absence of a consensus on their fundamental make-up. Digital twins originate…
europepmc
2025
置信度 0.80
-
Aim This study, aimed to determine the individual innovativeness levels of nursing students and their readiness levels for medical artificial intelligence and the relationship between these two variables. Background A healthcare team with innovative personalit…
europepmc
2025
置信度 0.80
-
Abstract Background With the rapid integration of artificial intelligence (AI) into medical education, assessing medical students’ readiness has become critical. This readiness encompasses not only familiarity with AI tools but also the ability to apply, evalu…
europepmc
Xuancheng Chen, Yangyi Chen, Yuhuan Xie, Linan Cheng
2025
置信度 0.80
-
Objective From the perspectives of algorithmic transparency and data security to establish a practical and feasible ethical review mechanism for medical artificial intelligence (AI) research, effectively safeguarding the life, health, personal dignity, and leg…
europepmc
2025
置信度 0.80
-
Objective To assess medical students' attitudes, knowledge, opinions, and expectations regarding medical artificial intelligence solutions, according to their sex and year of study. Methods This cross-sectional survey was a single-center study conducted at a m…
europepmc
2025
置信度 0.80
-
Introduction The integration of artificial intelligence (AI) in the United Kingdom's National Health Service may enhance patient care and alleviate systemic pressures. However, adoption of medical AI is challenged by limited educational access, low confidence …
europepmc
2025
置信度 0.80
-
To the Editor: The review by Yu et al. (May 30 issue) 1 misses a key point: with which specific human values should an artificial intelligence (AI) model be aligned? The question is essentially about fairness. 2,3 The alignment of AI with human values is not a…
europepmc
2024
置信度 0.80
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The integration of artificial intelligence (AI) into medical research poses significant challenges for Ethics Review Committees (ERCs), especially concerning clinical trials and ethical assessments. This review identifies 23 primary challenges ERCs encounter i…
europepmc
2025
置信度 0.80
-
This article reflects on explainability in the context of medical artificial intelligence (AI) applications, focusing on AI-based clinical decision support systems (CDSS). After introducing the concept of explainability in AI and providing a short overview of …
europepmc
Elisabeth Hildt
2025
置信度 0.80
Context (archaeology)Relevance (law)Clinical decision support systemArtificial intelligenceComputer science
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BACKGROUND: Large language models (LLMs) are being explored for disease prediction and diagnosis; however, their effi cacy for early sepsis identifi cation in emergency departments (EDs) remains unexplored.This study aims to evaluate MedGo, a novel medical LLM…
europepmc
Sen Jiang, Xiandong Liu, Tong Liu, Yi Gu 等
2025
置信度 0.80
MedicineSepsisMedical emergencyIntensive care medicineAcute medicine
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Aim This study was conducted to identify nursing students' medical artificial intelligence readiness and individual innovativeness levels, to examine the relationship between these two concepts and to determine the variables that create a significant differenc…
europepmc
2025
置信度 0.80
-
Many countries around the world do not collect race and ethnicity data in clinical settings. Without such identified data, it is difficult to identify biases in the training data or output of a given artificial intelligence (AI) algorithm, and to work towards …
europepmc
2025
置信度 0.80