Large Language Models in Healthcare and Medical Domain: A Review

Informatics, Journal Year: 2024, Volume and Issue: 11(3), P. 57 - 57

Published: Aug. 7, 2024

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These exhibit remarkable ability to provide proficient responses free-text queries, demonstrating a nuanced understanding professional medical knowledge. This comprehensive survey delves into functionalities existing LLMs designed for applications elucidates trajectory their development, starting with traditional Pretrained Language Models (PLMs) then moving present state in sector. First, we explore potential amplify efficiency effectiveness diverse applications, particularly focusing on clinical tasks. tasks encompass wide spectrum, ranging from named entity recognition relation extraction natural inference, multimodal document classification, question-answering. Additionally, conduct an extensive comparison most recent state-of-the-art domain, while also assessing utilization various open-source highlighting significance applications. Furthermore, essential performance metrics employed evaluate biomedical shedding light limitations. Finally, summarize prominent challenges constraints faced by offering holistic perspective benefits shortcomings. review provides exploration current landscape healthcare, addressing role transforming areas that warrant further research development.

Language: Английский

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Transparent AI Disclosure Obligations: Who, What, When, Where, Why, How

Published: May 2, 2024

Advances in Generative Artificial Intelligence (AI) are resulting AI-generated media output that is (nearly) indistinguishable from human-created content. This can drastically impact users and the sector, especially given global risks of misinformation. While currently discussed European AI Act aims at addressing these through Article 52's transparency obligations, its interpretation implications remain unclear. In this early work, we adopt a participatory approach to derive key questions based on disclosure obligations. We ran two workshops with researchers, designers, engineers across disciplines (N=16), where participants deconstructed relevant clauses using 5W1H framework. contribute set 149 clustered into five themes 18 sub-themes. believe not only help inform future legal developments interpretations 52, but also provide starting point for Human-Computer Interaction research (re-)examine human-centered lens.

Language: Английский

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Generative AI and data protection

Published: Jan. 1, 2025

Abstract Generative artificial intelligence (AI) has catapulted into the legal debate through popular applications ChatGPT, Bard, Dall-E and others. While predominant focus hitherto centred on issues of copyright infringement regulatory strategies, particularly in context AI Act, a critical but often overlooked issue lies friction between generative data protection laws. The rise these technologies highlights unresolved tension safeguarding fundamental rights vast, almost universal, scale processing required for machine learning. Large language models, which scrape nearly whole Internet rely may even generate personal falling under GDPR. This manifests across multiple dimensions, encompassing subjects’ rights, foundational principles categories protection. Drawing ongoing investigations by authorities Europe, this paper undertakes comprehensive analysis intricate interplay within European framework.

Language: Английский

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Biden’s Executive Order on AI and the E.U.’s AI Act: A Comparative Computer-Ethical Analysis

Philosophy & Technology, Journal Year: 2024, Volume and Issue: 37(3)

Published: June 19, 2024

Language: Английский

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Examining epistemological challenges of large language models in law

Published: Jan. 1, 2025

Abstract Large Language Models (LLMs) raises challenges that can be examined according to a normative and an epistemological approach. The approach, increasingly adopted by European institutions, identifies the pros cons of technological advancement. Regarding LLMs, main concern innovation, economic development achievement social goals values. disadvantages mainly cases risks harms generated means LLMs. approach examines how LLMs produce outputs, information, knowledge, representation reality in ways differ from those followed human beings. To face impact our paper contends should as priority: identifying opportunities also depends on considering this form artificial intelligence works point view. end, analysis compares epistemology with law, order highlight at least five issues terms of: (i) qualification ; (ii) reliability (iii) pluralism novelty (iv) dependence (v) relation truth accuracy . these issues, preliminary one, lays foundations better frame arising use

Language: Английский

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EU rules of origin, signalling and the potential erosion of the art market through generative artificial intelligence

Published: Jan. 1, 2025

Abstract Generative artificial intelligence (GenAI) systems generate artwork likely to be copyrightable if made by human. In lieu of discussing whether machine-enabled artworks should copyrighted, a question that has received large attention in academic scholarship, this paper proposes analyse the economic implications GenAI. Although valuation their outputs is still mostly unknown, preliminary studies show that, all other things being equal, humans’ works are evaluated at significant higher value than ones. Yet, properly valued, human-made and products must distinguishable. They not. This indistinguishability creates an asymmetry information turn leads lemons problem, defined as market erosion good-quality products. Against background, solution light European Union rules origin so-called substantial transformation test. can then used copyright law identify where human author been able make free creative choices (or lack thereof) required satisfy criterion originality and, hence, copyrightability.

Language: Английский

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Beyond Incompatibility: Trade-offs between Mutually Exclusive Fairness Criteria in Machine Learning and Law

Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 104280 - 104280

Published: Jan. 1, 2025

Language: Английский

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Saudi Arabia’s Generative AI Strategy: Legal Challenges in Intellectual Property Protection

Journal of Lifestyle and SDGs Review, Journal Year: 2025, Volume and Issue: 5(2), P. e04873 - e04873

Published: Jan. 30, 2025

Objectives: This study aims to evaluate Saudi Arabia’s legal framework concerning intellectual property (IP) protection in AI development. It seeks identify barriers training, particularly copyright law, and propose legislative reforms enhance innovation while maintaining IP rights. The research aligns with Vision 2030, positioning Arabia as a leader AI-driven innovation. Methods: employs comparative analysis, examining international models such the United States, European Union, Japan. assesses laws related identifying limitations due strict adherence conventions. also explores potential support Results: finds that lacks flexibility needed hinder training absence of exceptions for text data mining. Comparative analysis reveals other jurisdictions have adopted more adaptive licensing mechanisms open policies, which foster growth. Conclusion: concludes must implement balance recommends introducing mining, establishing models, promoting policies. Strengthening public-private partnerships is suggested facilitate lawful access. These are essential become regional global

Language: Английский

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Disinformation and Misinformation in the Age of Generative AI

Published: Feb. 26, 2025

Language: Английский

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Large language model for patent concept generation

Advanced Engineering Informatics, Journal Year: 2025, Volume and Issue: 65, P. 103301 - 103301

Published: March 31, 2025

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