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Littérature scientifique sur le sujet « AI powered patent tools »

Auteur : Grafiati

Publié le 2 juin 2025

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "AI powered patent tools"

Shahzeb Akhtar. "The Role of Artificial Intelligence in Enhancing Patent Lifecycle Management." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 2194–205. https://doi.org/10.32628/cseit23112582.

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This article explores the transformative role of Artificial Intelligence (AI) across the entire patent lifecycle, from initial ideation to post-grant management. It examines how AI technologies are revolutionizing various aspects of patent processes, including brainstorming and invention disclosure, prior art searches, patent drafting, office action responses, and portfolio management. The article discusses the potential of AI to enhance efficiency, accuracy, and strategic decision-making in patent management while also addressing the ethical and legal challenges that arise from integrating AI

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Mr., Mohd Abdul Muneim Farzaan. "Revolutionizing Patent Processes: The Rise of AI-Assisted Patent Prosecution." Annual International Journal on Analysis of Contemporary Legal Affairs (AIJACLA) 5 (May 26, 2025): 220–29. https://doi.org/10.5281/zenodo.15521506.

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<em>The rapid advancement of Artificial intelligence is transforming innovation across industries, including intellectual property (IP). AI generated inventions has become increasingly prevalent worldwide and are reshaping its traditional processes of patent Drafting, examination and enforcement. AI tools predict patentability and automate patent searches with high efficiency. These advancements enable patent professionals enhance their decision making. An AI system generates novel ideas and inventions for intellectual property rights and for patent purposes and it also helps in learning machi

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Deepa P., Badrinath P., Mohanaprasanth N., Pranesh S., and Sriram E. "AI-Powered Doctolib: Revolutionizing Healthcare Appointment Management." Asian Journal of Basic Science & Research 06, no. 04 (2024): 90–102. https://doi.org/10.38177/ajbsr.2024.6407.

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Healthcare systems face persistent challenges in managing appointments and improving accessibility, particularly in underserved regions. This paper explores the development and implementation of Doctolib, an AI-driven healthcare platform designed to address these issues. By utilizing advanced algorithms, real-time scheduling, and predictive analytics, Doctolib enhances the efficiency of appointment management. Key features include an AI chatbot for 24/7 patient support, secure telemedicine integration for remote consultations, and demand optimization tools to better allocate resources. The pla

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Zampatti, Stefania, Juliette Farro, Cristina Peconi, et al. "AI-Powered Neurogenetics: Supporting Patient’s Evaluation with Chatbot." Genes 16, no. 1 (2024): 29. https://doi.org/10.3390/genes16010029.

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Background/Objectives: Artificial intelligence and large language models like ChatGPT and Google’s Gemini are promising tools with remarkable potential to assist healthcare professionals. This study explores ChatGPT and Gemini’s potential utility in assisting clinicians during the first evaluation of patients with suspected neurogenetic disorders. Methods: By analyzing the model’s performance in identifying relevant clinical features, suggesting differential diagnoses, and providing insights into possible genetic testing, this research seeks to determine whether these AI tools could serve as a

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Vidushi, Sharma. "AI-Powered Automation in Healthcare: Improving Patient Care and Operational Efficiency." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 7, no. 4 (2019): 1–8. https://doi.org/10.5281/zenodo.14785680.

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Artificial Intelligence (AI) and automation technologies have become pivotal in transforming the healthcare sector, offering innovative solutions that enhance both patient care and operational efficiency. The integration of AI-powered automation can address several critical challenges faced by modern healthcare systems, including rising patient demand, resource limitations, and the increasing complexity of healthcare management. AI-driven systems provide opportunities to automate routine tasks, improve diagnostic accuracy, optimize clinical workflows, and deliver personalized treatment plans b

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Akter, Sharmin, MD Sheam Arafat, Kirtibhai Desai, Mir Abrar Hossain, and Ayesha Islam Asha. "AI-Powered Computing Racks: Transforming Healthcare IT with Faster Diagnostics and Intelligent Data Processing." American Journal of Applied Sciences 07, no. 05 (2025): 07–30. https://doi.org/10.37547/tajas/volume07issue05-02.

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Healthcare IT underwent a revolution through artificial intelligence (AI) together with high-performance computing which particularly enhances diagnostics along with intelligent data processing operations. The use of AI-powered computing racks delivers exceptional speed alongside efficiency for handling large-scale medical data which leads to faster diagnoses and real-time patient observation and precise medical treatments. This paper studies how AI-powered computing racks redefine healthcare IT operations through their ability to boost computational power and generate more accurate diagnoses

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Basnawi, Abdullah, and Ahmad Koshak. "Application of Artificial Intelligence in Advanced Training and Education of Emergency Medicine Doctors: A Narrative Review." Emergency Care and Medicine 1, no. 3 (2024): 247–59. http://dx.doi.org/10.3390/ecm1030026.

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Emergency medicine (EM) demands continuous adaptation and refinement of training methodologies to equip healthcare professionals with the expertise to effectively manage complex and time-sensitive patient presentations. Artificial intelligence (AI), with its remarkable ability to process vast amounts of data, identify patterns, and make predictions, holds immense promise for enhancing the advanced training and education of EM physicians. This narrative review aims to discuss the potential of AI in transforming EM training and highlight the specific applications of AI in personalized learning,

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A R, SALIM MALIK. "AI Continues to be a Game Changer in the Intellectual Property Management in India." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41289.

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The integration of Artificial Intelligence (AI) into Intellectual Property (IP) management has significantly reshaped the landscape of IP administration in India. With the growing emphasis on innovation and technological advancement, India's IP ecosystem is rapidly adopting AI-driven solutions to streamline processes, enhance accuracy, and reduce human intervention. AI-powered tools for prior art searches, patent classification, and infringement detection have significantly accelerated IP workflows while reducing the backlog of pending applications. This paper explores the transformative role

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Saroj Kumar Rout. "Enhancing Clinical Communication through AI-Powered Recording and Analysis: A Multi-Center Study of Scribr AI Implementation." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1170–78. https://doi.org/10.32628/cseit241061158.

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This article examines the implementation and effectiveness of Scribr AI, an artificial intelligence-powered system designed to enhance doctor-patient communication through automated recording, transcription, and multilingual support in clinical settings. The article evaluates the platform's impact on clinical documentation, patient comprehension, and longitudinal care management across multiple healthcare facilities. Through a comprehensive article analysis of system usage, patient engagement, and healthcare provider feedback, the article demonstrates significant improvements in communication

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Bajhzer, Rahaf, Mona Alghamdi, and Salma Elhag. "AI Powered Bioinformatics - Expediting Diagnostic Testing: A Survey." International Journal of Computers and Informatics 3, no. 9 (2024): 22–52. http://dx.doi.org/10.59992/ijci.2024.v3n9p2.

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Research has demonstrated the positive impact of artificial intelligence and Bioinformatics in the field of clinical diagnosis. The integration of AI methodologies into bioinformatics has opened new avenues for breakthroughs in genomics, proteomics, and personalized medicine. The document emphasizes the role of AI in early disease detection, improving patient outcomes, and enhancing healthcare systems by avoiding the need for expensive and time-consuming operations as illnesses worsen. The methodology section provides insights into the approach utilized, including the review of 30 articles fro

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Chapitres de livres sur le sujet "AI powered patent tools"

Osmanoglu, Usame Omer. "The Use of Artificial Intelligence in the Diagnosis and Treatment of Diabetes." In Current Multidisciplinary Approach to Diabetes Mellitus Occurrence Mechanism. Nobel Tip Kitabevleri, 2023. http://dx.doi.org/10.69860/nobel.9786053359104.15.

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Artificial intelligence (AI) is increasingly transforming the landscape of diabetes diagnosis and treatment by leveraging data-driven approaches to enhance precision and efficiency in healthcare. AI algorithms analyze vast amounts of patient data, including medical records, genetic profiles, and real-time physiological metrics from wearable devices, to identify patterns and predict disease progression. In diagnostics, AI-powered systems can interpret complex datasets to facilitate early detection of diabetes and its complications, such as diabetic retinopathy and nephropathy, improving clinica

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Eager, Bron. "Towards responsible use of AI tools." In AI-Powered Scholar. Routledge, 2024. http://dx.doi.org/10.4324/9781032665276-7.

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Kansal, Aarushi. "Chains, Tools and Agents." In Building Generative AI-Powered Apps. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0205-8_3.

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Kanthimathi, S., Prayasha Nanda, Shravan Venkatraman, Varsana Renganayagan, and Sivaraman Eswaran. "Transforming Education through AI-Powered Personalized Assessment Models." In Adopting Artificial Intelligence Tools in Higher Education. CRC Press, 2025. https://doi.org/10.1201/9781003470304-7.

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Gupta, Ram Gopal, Ankur Dumka, and Bireshwar Dass Mazumdar. "AI-Powered Automation Tools for Software Product Checking and Cost Management." In AI for Product Development. CRC Press, 2025. https://doi.org/10.1201/9781003536901-13.

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Antipova, Tatiana, Simona Riurean, Patricia Riurean, and George Bolog. "AI-Powered Tools: Threat, Defense, and Cyber-Resilience for Individuals." In Information Systems Engineering and Management. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-86547-3_14.

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Mathur, Anjali. "Enhancing Learning Outcomes for the Dyslexic Students Using AI-Powered Assistants." In Adopting Artificial Intelligence Tools in Higher Education. CRC Press, 2025. https://doi.org/10.1201/9781003470304-6.

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Karahan, Hanım Gülsüm, Begüm Aktaş, and Cemal Koray Bingöl. "Use of Language to Generate Architectural Scenery with AI-Powered Tools." In Communications in Computer and Information Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37189-9_6.

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Tariq, Muhammad Usman. "AI-Powered Breakthroughs." In Advances in Psychology, Mental Health, and Behavioral Studies. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9341-3.ch003.

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This chapter examines how artificial intelligence (AI) is improving neuropsychological practice and how AI tools can be used to diagnose treat and rehabilitate cognitive disorders. Through a critical analysis of recent research and developing patterns the chapter emphasizes AIs potential for neuropsychology real-time interventions personalized care and early detection. It explores how artificial intelligence (AI) has advanced to create tools like virtual assistants chatbots and machine learning algorithms that have greatly enhanced neuropsychological testing and treatment. AI in neurorehabilit

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Narayanan, Lakshmi Kanthan, Priyanga Subbiah, Rengaraj Alais Muralidharan R., and Senthil Balaji V. "Smart AI-Powered Wearable Sensors for Pregnant Women." In Technological Tools for Predicting Pregnancy Complications. IGI Global, 2023. http://dx.doi.org/10.4018/979-8-3693-1718-1.ch004.

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Information and communication technology today enables health organizations to contact marginalized people in remote areas using sensing and artificial intelligence technologies. Applications of these technologies are even more crucial for maternal and newborn health because they are essential for a healthy society. Over the past few years, scientists have been researching sensing and artificially intelligent healthcare systems for mother and baby health. Sensors are utilized to monitor patient health parameters. The wearable sensors and AI algorithms mentioned in this chapter are based on exi

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Actes de conférences sur le sujet "AI powered patent tools"

Babushkin, Konstantin, Nikolai Timofeev, and Ivan Filianin. "Research on AI-Powered Employee Feedback Tools." In 2025 International Russian Smart Industry Conference (SmartIndustryCon). IEEE, 2025. https://doi.org/10.1109/smartindustrycon65166.2025.10986092.

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Kushnarevych, Andrii. "Building Loyalty Programs with AI-Powered Online Tools." In 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI). IEEE, 2024. https://doi.org/10.1109/cinti63048.2024.10830833.

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Pesovski, Ivica, Daniela Vorkel, and Vladimir Trajkovik. "AI-Powered Education: Rethinking the Way Programming is Taught Using AI Tools and Reversed Bloom's Taxonomy." In 2024 21st International Conference on Information Technology Based Higher Education and Training (ITHET). IEEE, 2024. https://doi.org/10.1109/ithet61869.2024.10837604.

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Delgado-Solorzano, Cecilia, and Carlos Toxtli. "The Use of AI-powered Language Tools in Crowdsourcing to reduce Language Barriers." In 2024 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics. IEEE, 2024. http://dx.doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics62450.2024.00110.

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Hussain, Mumtaz, and Tariq Rahim Soomro. "AI-Powered Cybercrime: A Survey on Emerging Threats, Tools & Techniques for Countermeasures." In 2024 26th International Multitopic Conference (INMIC). IEEE, 2024. https://doi.org/10.1109/inmic64792.2024.11004322.

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Maltseva, Svetlana N., and Anna Y. Pavlova. "Analyzing the Potential of AI-Powered Writing Evaluation Tools for Developing Students' Analytical Skills." In 2025 Systems of Signals Generating and Processing in the Field of on Board Communications. IEEE, 2025. https://doi.org/10.1109/ieeeconf64229.2025.10948096.

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Das, Jiban Krisna, Ifeoluwa Elegbe, Lord Coffie, Rojeena Khadka, Lei Chen, and Yiming Ji. "AI-Powered IT Project Management: Analyzing the Effectiveness of Advanced Project Management Tools to Ensure Project Efficiency." In SoutheastCon 2025. IEEE, 2025. https://doi.org/10.1109/southeastcon56624.2025.10971718.

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Pouliou, Panagiota, George Palamas, and Anca-Simona Horvath. "Decisions we Should put in the Algorithm: Mapping Architects’ Attitudes Towards Computational and AI-Powered Tools for Practice." In CAADRIA 2024: Accelerated Design. CAADRIA, 2024. http://dx.doi.org/10.52842/conf.caadria.2024.3.049.

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Lioupi, Chrysanthi, and Georgios Fevgas. "Military Psychological Therapies in a New Era: Advancements through AI-Powered Interventions." In 5th World Conference on Psychology and Behavioral Science. Eurasia Conferences, 2024. https://doi.org/10.62422/978-81-974314-9-4-003.

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Integrating Large Language Models (LLMs) into military mental health care significantly enhances therapeutic practices for service members confronting unique psychological challenges. This presentation examines the innovative application of LLMs in psychotherapy, particularly their utility in assisting military psychologists with initial clinical assessments and patient interactions. By training LLMs on military-specific case studies, these models can effectively decipher complex psychological patterns, relational dynamics, and stressors inherent to military life, including combat trauma, rein

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Filipović, Nenad. "Artificial intelligence-based decision support system for risk stratification and early detection of heart failure in primary and secondary care." In Proceedings of the International Congress Public Health - Achievements and Challenges. Institute of Public Health of Serbia "Dr Milan Jovanović Batut", 2024. http://dx.doi.org/10.5937/batutphco24006f.

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Heart failure is a multifaceted clinical syndrome that impacts over 15 million individuals throughout Europe. It is closely linked with diminished quality of life for patients and substantial healthcare expenditures. Consequently, pioneering AI tools can expedite the initiation of preventive and therapeutic approaches. The EU-funded STRATIFYHF project will develop, validate and implement an AI-driven decision support system through server and mobile-app. This system will serve the purpose of risk stratification, early detection and evaluation of disease progression, effectively addressing the

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Rapports d'organisations sur le sujet "AI powered patent tools"

Leger, Dorian. Pre-registration: Landscape Review of AI-Powered Research Tools for Literature Review and Discovery. ResearchHub Technologies, Inc., 2025. https://doi.org/10.55277/researchhub.e7ni6r9s.

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Jakobsen, Tor Georg. Using ChatGPT with Stata: Regression Analysis (Part II). Instats Inc., 2025. https://doi.org/10.61700/2w5b85mmn916t1568.

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This comprehensive 3-day workshop focuses on refining statistical modeling and regression analysis skills by integrating advanced AI tools like ChatGPT with traditional software such as Stata. Participants will gain practical competencies in various regression techniques, including interaction effects (or 'moderation'), logistic regression, missing data, scale construction, transformations, weighting, and how to deal with regression assumptions, along with AI-powered assistance from ChatGPT to clarify concepts and troubleshoot commands.

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Pasupuleti, Murali Krishna. Decentralized Creativity: AI-Infused Blockchain for Secure and Transparent Digital Innovation. National Education Services, 2025. https://doi.org/10.62311/nesx/rrvi125.

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Abstract The convergence of artificial intelligence (AI) and blockchain technology is transforming the creative economy by enabling secure, transparent, and decentralized innovation in digital content creation, intellectual property management, and monetization. Traditional creative industries are often constrained by centralized platforms, opaque copyright enforcement, and unfair revenue distribution, which limit the autonomy and financial benefits of creators. By leveraging blockchain’s immutable ledger, smart contracts, and non-fungible tokens (NFTs), digital assets can be authenticated, to

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Felix, Juri, and Laura Webb. Use of artificial intelligence in education delivery and assessment. Parliamentary Office of Science and Technology, 2024. http://dx.doi.org/10.58248/pn712.

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This POSTnote considers how artificial intelligence (AI) technologies can be used by educators and learners in schools, colleges and universities. Artificial intelligence technologies that can be used in education have developed rapidly in recent years. This has been driven in part by advancements of generative AI, which is now capable of performing a wide range of tasks including the production of realistic content such as text, images, audio and video. Artificial intelligence tools have the potential to provide different ways of learning and to help educators with lesson planning, marking an

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