Results 81 to 90 of about 12,895,403 (289)

Generative Artificial Intelligence in Clinical Practice: How Should Rheumatologists Evaluate and Monitor Emerging Tools?

Arthritis Care &Research, EarlyView.
Generative artificial intelligence (AI) is increasingly being used in rheumatology practice, to assist with tasks such as documentation, record summarization, and clinical decision support. Rheumatologists need a practical approach to determining what evidence and oversight each application requires.
Koushan Kouranloo, Mrinalini Dey, Jinoos Yazdany   +2 more
wiley   +1 more source

Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing; FAIM 2014 [PDF]

, 2014
Paper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of
Machač, Jan; Steiner, František, František Steiner, Steiner, Frantisek, Jan Machač, Machac, Jan   +4 more
core   +3 more sources

Life cycle assessment of benzoxazinone synthesis: Comparative evaluation of alternative synthetic pathways

Cleaner Engineering and Technology
A cradle-to-gate life cycle assessment (LCA) of benzoxazinone (BZ) synthesis along two known routes, the two-step benzoxazinone route (TS-BZ) and the TCT-activated benzoxazinone route (TCT-BZ), is reported in this study.
Anuchit Wuttitrairat, Wasan Kongnaikhaw, Soottiwan Thamsakon, Wachira Daosud, Weerawun Weerachaipichasgul, Paisan Kittisupakorn   +5 more
doaj   +1 more source

Artificial Intelligence‐Driven Extraction of Patient‐Reported Pain Outcomes in Osteoarthritis Using Large Language Models

Arthritis Care &Research, Accepted Article.
Objective Patient‐reported outcome measures (PROMs) are central to assessing symptom burden and treatment response in Osteoarthritis (OA) but are often embedded in unstructured clinical notes. We evaluated whether prompt‐engineered large language models (LLMs) could accurately extract or infer pain scores on a 0‐10 scale from routine OA clinical ...
Jainesh Doshi, Stephen Batter, Yiyuan Wu, William Salerno, Alice Santilli, Sandhya Kannayiram, Susan Goodman, Bella Mehta   +7 more
wiley   +1 more source

Life cycle assessment of converting waste plastics into activated carbon: A comparative analysis of HDPE, LDPE, PS, and PP feedstocks

Cleaner Environmental Systems
Activated carbon (AC) is an important adsorbent for environmental treatment; however, the traditional method of production is energy-consuming and chemical-intensive. AC from valorized post-consumer plastics is a promising waste-to-resource route.
Anuchit Wuttitrairat, Soottiwan Thamsakon, Wachira Daosud, Paisan Kittisupakorn   +3 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Intelligent process automation and its relevance to various industries

Intelligent process automation represents a significant leap forward in the integration of artificial intelligence and robotic process automation to streamline and enhance various business operations.
Park, Jin Yong, Kandasamy, R., Thangam, D., Patil, Shashikala, K. A., Pavan, Chikkandar, R.   +5 more
core   +1 more source

Turning Robotic Process Automation onto Intelligent Automation with Machine Learning

, 2023
Robotic Process Automation (RPA) technology has in the past few years become a ground-breaking trend that revolutionised services all around the globe.
Kedziora, Damian, Hyrynsalmi, Sami
core   +1 more source

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

Advanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad, Saurabh Thorat, Andre Loch Gesing, Dominik Huber, Christopher Zellner, Patrick Egger, Georg Pfusterschmied, Ulrich Schmid, Michael Schneider   +8 more
wiley   +1 more source

Research progress of automation and digitalization in brewing process of Baijiu [PDF]

Zhongguo niangzao
Baijiu is a unique distilled spirit in China. Its complex and distinctive brewing process has given rise to different style characteristics. Against the backdrop of industrial intelligence, traditional Baijiu brewing is also confronted with both ...
YU Zihan, LI Qingliang, LU Yanxiang, LI Jianxun, ZHANG Jing, ZHOU Die, REN Xintong, FEI Wangwang, CHEN Peng
doaj   +1 more source