24 papers · ranked by Valyu relevance
Daniel Jönsson, Mattias Tiger, Stefan Ekberg, Daniel Jakobsson + 2 more
We outline a comprehensive framework for artificial intelligence (AI) Application Operations (AIAppOps), based on real-world experiences from diverse organizations. Data-driven projects pose additional challenges to organizations due to their dependency on data across the development and operations cycles. To aid…
Muhammad Usman Tariq, Marc Poulin, Abdullah A. Abonamah
This paper presents an in-depth literature review on the driving forces and barriers for achieving operational excellence through artificial intelligence (AI). Artificial intelligence is a technological concept spanning operational management, philosophy, humanities, statistics, mathematics, computer sciences, and…
Sharareh Shahidi Hamedani, Sarfraz Aslam, Shervin Shahidi Hamedani
The intersection of AI role and business operations has recently gained widespread attention. Some studies (Chen et al., ; Shahzadi et al., ) focused on AI's role in supply chain management, highlighting its role in minimizing inefficiencies and improving logistics by utilizing AI more often; supply chains become…
Marc Schmitt
The integration of Artificial Intelligence (AI) into corporate strategy has become a pivotal focus for organizations aiming to maintain a competitive advantage in the digital age. As AI reshapes business operations and drives innovation, the need for specialized leadership to effectively manage these changes becomes…
Dmitry Mikhailov
—As artificial intelligence and machine learning continue to advance, we must understand their strategic importance in national security. This paper focuses on unique AI applications in the military, emphasizes strategic imperatives for success, and aims to rekindle excitement about AI's role in national security. We…
Andrew Wong, Brahmajee K. Nallamothu, Christopher A. Longhurst, Karandeep Singh
Despite the potential of AI to improve healthcare delivery, healthcare has lagged behind other sectors in its adoption of operational AI technologies. To address this gap, we outline examples of successful AI applications from other sectors, draw parallels to healthcare, and provide a roadmap for health system leaders…
Rune Møberg Jacobsen, Joel Wester, Helena Bøjer Djernæs, Niels van Berkel
'Niels van Berkel'] This paper investigates the impact of artificial intelligence integration on remote operations, emphasising its influence on both distributed and team cognition. As remote operations increasingly rely on digital interfaces, sensors, and networked communication, AI-driven systems transform…
Authors not listed
Artificial intelligence (AI) is reshaping scientific research by accelerating discovery and enabling the analysis of complex data that traditional methods struggle to handle. This review examines over 310,000 journal articles and patents from the CAS Content Collection (2015–2025), with a focus on, biomedical research…
Sarab Anand, Marco Tagliafierro, Ali Fatehi Hassanabad, Marco Pirelli + 1 more
Recent evidence in the literature suggests that Artificial intelligence (AI) is rapidly becoming more clinically relevant with expanding applications across cardiovascular medicine and cardiothoracic surgery. Advances in computational power and the widespread digitization of clinical data have enabled AI models to…
Gavin Pearson, Phil Jolley, Geraint Evans
The current resurgent interest in Artificial Intelligence (AI) has been driven by the availability of data (particularly labelled data), the democratisation of computing infrastructure and tooling, and the ability to combine these elements to create AI algorithms. Benefit is achieved once an algorithm is deployed into…
Zhichu Ren, Zhen Zhang, Yunsheng Tian, Ju Li
Autonomous laboratories were previously controlled mainly by scripting languages such as Python, limiting their usage among experimentalists. The recent release of OpenAI's ChatGPT API's function calling feature has enabled seamless integration and execution of Python subroutines in experimental workflows using voice…
Alexander Muacevic, John R Adler, Vincent Weidlich, Georg A. Weidlich
'Georg A. Weidlich'] Artifical Intelligence (AI) was reviewed with a focus on its potential applicability to radiation oncology. The improvement of process efficiencies and the prevention of errors were found to be the most significant contributions of AI to radiation oncology. It was found that the prevention of…
Ata Mohajer-Bastami, Sarah Moin, Suhaib Ahmad, Ahmed R. Ahmed + 21 more
Objectives This narrative review evaluates the role of artificial intelligence (AI) in healthcare, summarizing its historical evolution, current applications across medical and surgical specialties, and implications for allied health professions and biomedical research. Methods We conducted a structured literature…
Authors not listed
This article proposes a three-level classification of artificial intelligence (AI) application in chemical sciences, reflecting the increasing degree of technology involvement in scientific and production processes: from automation of routine tasks (the level of "AI Assistant"), to the creation of specialized…
Shuo Yang, Huimin Lu
Welcome to the UK-RAS White Paper Series on Robotics and Autonomous Systems (RAS). This is one of the core activities of UK-RAS Network, funded by the Engineering and Physical Sciences Research Council (EPSRC). By bringing together academic centres of excellence, industry, government, funding bodies and charities, the…
Alexander Muacevic, John R Adler, Nicolás Idárraga Ruiz, Israel Cardona Salazar + 4 more
This narrative literature review synthesized evidence to address gaps in knowledge regarding AI performance and its integration into surgical operations. The purpose of the review was to assess AI accuracy and reliability, benchmark real-time guidance technologies, identify data and ethical issues, compare model…
Authors not listed
Artificial intelligence (AI) is reshaping chemical engineering. Still, its role in safety-critical operations is limited because we rarely see tools that link physical models with data-driven methods. This study brings together three elements: physics-constrained neural networks, uncertainty quantification, and a…
Hongwei Cai, Zheng Ao, Chunhui Tian, Zhuhao Wu + 5 more
Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we…
Mohammed O. Ahmed, Sahil A. Amale, Rhythm D. Bhavsar, Pratham Chopra + 18 more
Artificial Intelligence (AI) frameworks for automating scientific research have shown strong performance on benchmarks, but their capacity to routinely reproduce results from multiple real-life published studies remains largely untested. We evaluated five advanced AI research frameworks (Kosmos, K-Dense, ToolUniverse…
Marcel van Gerven
New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong…
Satvik Tripathi, Alisha Isabelle Augustin, Farouk Dako, Edward Kim
Because of the growing need to provide better global healthcare, computer-based and robotic healthcare equipment that depend on artificial intelligence have seen an increase in development. In order to evaluate artificial intelligence (AI) in computer technology, the Turing test was created. For evaluating the future…
Scott Spillias, Jacob Rogers, Fabio Boschetti, Beth Fulton + 3 more
Ecosystem models are essential for ecosystem management, but their development traditionally requires significant time and expertise, creating bottlenecks in addressing urgent environmental challenges. We present “AI for Models of Ecosystems” (AIME), a novel framework that integrates large language models (LLMs) with…
Tomiko Oskotsky, Ruchika Bajaj, Jillian Burchard, Taylor Cavazos + 15 more
Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to flawed systems that perpetuate gender and racial biases, and limit how broadly AI can help people. The UCSF AI4ALL program…
Authors not listed
As the utilization of artificial intelligence (AI) and generative AI (GenAI) is expanding in the educational field, presenting significant implications for STEM disciplines, it is bringing opportunities to enhance how chemistry and chemical engineering are taught and learned. This perspective critically explores the…