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Articles 421 - 450 of 1810
Full-Text Articles in Entire DC Network
Unveiling The Potential Of Generative Artificial Intelligence: A Multidimensional Journey Into The Future, Keng Boon Ooi, Alex Koohang, Eugene Cheng Xi Aw, Tat Huei Cham, Cihan Cobanoglu, Charles Dennis, Yogesh K. Dwivedi, Jun Jie Hew, Heather Linton Kelly, Laurie Hughes, Chieh Yu Lin, Anubhav Mishra, Ian Phau, Ramakrishnan Raman, Marianna Sigala, Yun Chia Tang, Lai Wan Wong, Garry Wei Han Tan
Unveiling The Potential Of Generative Artificial Intelligence: A Multidimensional Journey Into The Future, Keng Boon Ooi, Alex Koohang, Eugene Cheng Xi Aw, Tat Huei Cham, Cihan Cobanoglu, Charles Dennis, Yogesh K. Dwivedi, Jun Jie Hew, Heather Linton Kelly, Laurie Hughes, Chieh Yu Lin, Anubhav Mishra, Ian Phau, Ramakrishnan Raman, Marianna Sigala, Yun Chia Tang, Lai Wan Wong, Garry Wei Han Tan
Research outputs 2022 to 2026
Purpose: The launch of ChatGPT has brought the large language model (LLM)-based generative artificial intelligence (GAI) into the spotlight, triggering the interests of various stakeholders to seize the possible opportunities implicated by it. Nevertheless, there are also challenges that the stakeholders should observe when they are considering the potential of GAI. Given this backdrop, this study presents the viewpoints gathered from various subject experts on six identified areas. Design/methodology/approach: Through an expert-based approach, this paper gathers the viewpoints of various subject experts on the identified areas of tourism and hospitality, marketing, retailing, service operations, manufacturing and healthcare. Findings: The subject …
Deep Learning-Based Superconductivity Prediction And Experimental Tests, Daniel Kaplan, Adam Zheng, Joanna Blawat, Rongying Jin, Robert J. Cava, Viktor Oudovenko, Gabriel Kotliar, Anirvan M. Sengupta, Weiwei Xie
Deep Learning-Based Superconductivity Prediction And Experimental Tests, Daniel Kaplan, Adam Zheng, Joanna Blawat, Rongying Jin, Robert J. Cava, Viktor Oudovenko, Gabriel Kotliar, Anirvan M. Sengupta, Weiwei Xie
Faculty Publications
The discovery of novel superconducting materials is a long-standing challenge in materials science, with a wealth of potential for applications in energy, transportation and computing. Recent advances in artificial intelligence (AI) have enabled expediting the search for new materials by efficiently utilizing vast materials databases. In this study, we developed an approach based on deep learning (DL) to predict new superconducting materials. We have synthesized a compound derived from our DL network and confirmed its superconducting properties in agreement with our prediction. Our approach is also compared to previous work based on random forests (RFs). In particular, RFs require knowledge …
Do Ais Dream Of Electric Boards?, Robert J. Rhee
Do Ais Dream Of Electric Boards?, Robert J. Rhee
Northwestern University Law Review
When artificial intelligence (AI) acquires self-awareness, agency, and unique intelligence, it will attain ontological personhood. Management of firms by AI would be technologically and economically feasible. The law could confer upon AI the status of legal personhood, as it did upon traditional business firms in the past, thus dispensing with the need for inserting AI as property within the legal boundary of a firm. As a separate and distinct entity, AI could function independently as a manager in the way that legal or natural persons do today: i.e., AI as director, officer, partner, member, or manager. Such a future is …
Artificial Intelligence For The Detection Of Acute Myeloid Leukemia From Microscopic Blood Images; A Systematic Review And Meta-Analysis, Feras Al-Obeidat, Wael Hafez, Asrar Rashid, Mahir Khalil Jallo, Munier Gador, Ivan Cherrez-Ojeda, Daniel (Centro De Investigación De Salud Pública Y Epidemiología Clínica Simancas-Racines, , Universidad Ute, Quito, Ecuador , Universidad Ute, Quito, Ecuador
Artificial Intelligence For The Detection Of Acute Myeloid Leukemia From Microscopic Blood Images; A Systematic Review And Meta-Analysis, Feras Al-Obeidat, Wael Hafez, Asrar Rashid, Mahir Khalil Jallo, Munier Gador, Ivan Cherrez-Ojeda, Daniel (Centro De Investigación De Salud Pública Y Epidemiología Clínica Simancas-Racines, , Universidad Ute, Quito, Ecuador , Universidad Ute, Quito, Ecuador
All Works
Leukemia is the 11th most prevalent type of cancer worldwide, with acute myeloid leukemia (AML) being the most frequent malignant blood malignancy in adults. Microscopic blood tests are the most common methods for identifying leukemia subtypes. An automated optical image-processing system using artificial intelligence (AI) has recently been applied to facilitate clinical decision-making. To evaluate the performance of all AI-based approaches for the detection and diagnosis of acute myeloid leukemia (AML). Medical databases including PubMed, Web of Science, and Scopus were searched until December 2023. We used the “metafor” and “metagen” libraries in R to analyze the different models used …
Data Literacy In The Age Of Artificial Intelligence: A Hermeneutic Phenomenological Study, Morgan V. Harrell
Data Literacy In The Age Of Artificial Intelligence: A Hermeneutic Phenomenological Study, Morgan V. Harrell
Doctoral Dissertations and Projects
The purpose of this hermeneutical phenomenological study is to explore the essential data and digital literacies for instructors in community colleges, trade schools, and vocational training programs located in the South to work with artificial intelligence (AI) effectively. The theory guiding this study is based on Max van Manen's framework on lived experiences and Paul Ricoeur's narrative theory, which is designed to enhance understanding of the perception and implementation of these literacies within an AI-augmented educational domain. As society's reliance on data continues to grow, it becomes essential to equip all citizens with the skills required for data literacy (Wolff …
Integrating Medical Plastic Waste Pyrolysis And Circular Economy For Environmental Sustainability, Attia Attia, Mohamed Bassyouni Prof., Reem Nasser Eng., Moataz El-Bagoury Eng., Islam Shaker Eng., Yasser Elhenawy Prof., Dina Aboelela Dr.
Integrating Medical Plastic Waste Pyrolysis And Circular Economy For Environmental Sustainability, Attia Attia, Mohamed Bassyouni Prof., Reem Nasser Eng., Moataz El-Bagoury Eng., Islam Shaker Eng., Yasser Elhenawy Prof., Dina Aboelela Dr.
Biochemical Engineering
A critical assessment of pyrolysis technologies and reactor designs was discussed, highlighting various reactor configurations. This study explored the influence of catalysts, temperature, heating rate, and residence time on the pyrolysis process, and addressed their effects on product distribution and composition. Safety considerations and strategies for mitigating the potential environmental impacts of pyrolysis were presented. Comparative analyses of the environmental impacts of traditional waste disposal methods versus pyrolysis-based approaches provided insights into the potential reduction of greenhouse gas emissions and other pollutants. The circular economy approach was explored in the context of medical plastic waste pyrolysis. The potential for closing …
Artificial Intelligence In Health Care: Business Opportunities And Ethical Challenges, Ankita Srivastava,, Marco Marabelli, Jeffrey Moriarty
Artificial Intelligence In Health Care: Business Opportunities And Ethical Challenges, Ankita Srivastava,, Marco Marabelli, Jeffrey Moriarty
Ethics Publication
Artificial intelligence (AI), and in particular generative AI (GAI), are making incredible progress toward automation. The pervasive and invasive nature of these technologies are affecting every industry, and health care is no exception. This paper summarizes insights derived from a panel that the Hoffman Center for Business Ethics and the Center for Health and Business at Bentley University hosted in March 2024. The panel invited three qualified health care professionals: Evan Carey, Susan Persky and John Torous. The panelists are all active in multiple aspects of AI in health care but represent a focus on the key areas of policy …
Ai 101: What It Can (And Can't) Do For You, April Sheppard
Ai 101: What It Can (And Can't) Do For You, April Sheppard
Staff and Faculty Scholarship
In this presentation, April defines AI, describes how it works, reviews some pros and cons, and finally discusses what AI can actually accomplish in its current iteration.
The Impacts Of Artificial Intelligence In Radiology, Misty Farmer, Wendy Trzyna
The Impacts Of Artificial Intelligence In Radiology, Misty Farmer, Wendy Trzyna
Theses, Dissertations and Capstones
Introduction: There has been significant growth in the use of Artificial Intelligence (AI) in the healthcare industry, especially in Medical Imaging. Radiology has been the clear frontrunner in the adoption of AI in medicine, due in part to the massive amount of digital data available for use in Deep Learning (DL) AI integration has the potential to solve multiple challenges in radiology, address workload issues and transform the field.
Purpose of the Study: The purpose of the research was to evaluate the impact of implementing Artificial Intelligence in radiology to determine if these technologies have had an impact …
Profile: Innovation Through The Liberal Arts, Communications And Marketing
Profile: Innovation Through The Liberal Arts, Communications And Marketing
Profile (1996-)
In this issue: Alumnus Chooses to Pay It Forward with Scholarships ; Gallant Makes the Most of Scholarships ; Newell Gives Back with Entrepreneurship Class ; Giving Allows Students to Get Business Ownership Experience ; Competitive Ethics Team Earns National Bid ; Tollefsrud Named Fulbright Finalist ; Noujdi Receives 2024 Undergraduate SEED Award ; Faculty and Staff Awards ; Hands-On Observatory Experience for Physics Students ; Zavada, Students Travel to Peru for Fulbright Research ; Morris Model Wins Second Department of Energy Competition ; 2025 Commencement ; Spotlight: Highlighting the Degree in Three Option ; AI Philosophy Tutor: Using AI …
Successfully Navigating The Disruption Ai Will Bring To Survey Research, David M. Rothschild, Trent D. Buskirk, Stephanie Eckman, D. Sunshine Hillygus, Frauke Kreuter, David Lazer
Successfully Navigating The Disruption Ai Will Bring To Survey Research, David M. Rothschild, Trent D. Buskirk, Stephanie Eckman, D. Sunshine Hillygus, Frauke Kreuter, David Lazer
Information Technology & Decision Sciences Faculty Publications
Surveys are a core methodological tool in government, industry, and academia, providing essential data for theory development and evidence-based decision-making. As artificial intelligence continues its rapid advancement, it stands to fundamentally transform the entire survey lifecycle - from design and administration to analytics and reporting. Previous transitions to new technologies, such as telephone, internet, and non-probability surveys, led to divisions within the survey research community with real consequences for both the trajectory of research and trust in the industry. We believe the survey community should take proactive steps now to avoid similar challenges with AI integration. Specifically, our paper examines …
Reimagining Compliance: Explainable Ai Models For Financial Regulatory Audits, Hrishikesh Desai
Reimagining Compliance: Explainable Ai Models For Financial Regulatory Audits, Hrishikesh Desai
Faculty Publications
This chapter develops an analytical model for Explainable AI (XAI) designed to support major types of banking regulatory compliance audits. Financial institutions increasingly rely on AI for efficiency in compliance tasks, but the opacity of complex models creates challenges in meeting regulatory transparency requirements. The proposed mathematical framework incorporates explainability as a quantifiable constraint in the optimization of AI models across five critical audit categories: CAMELS examinations, BSA/AML compliance, Consumer Compliance, IT Audits, and Internal Audits. By quantifying explainability through information- theoretic measures and Shapley values, the model balances predictive performance with regulatory requirements. The methodology is validated through a …
Maritime Industry Cybersecurity Threats In 2025: Advanced Persistent Threats (Apts), Hacktivism And Vulnerabilities, Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Mihaela Hnatiuc, Gabriel Raicu
Maritime Industry Cybersecurity Threats In 2025: Advanced Persistent Threats (Apts), Hacktivism And Vulnerabilities, Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Mihaela Hnatiuc, Gabriel Raicu
Engineering Management & Systems Engineering Faculty Publications
Background: The maritime industry, vital for global trade, faces escalating cyber threats in 2025. Critical port infrastructures are increasingly vulnerable due to rapid digitalization and the integration of IT and operational technology (OT) systems. Methods: Using 112 incidents from the Maritime Cyber Attack Database (MCAD, 2020-2025), we developed a novel quantitative risk assessment model based on a Threat-Vulnerability-Impact (T-V-I) framework, calibrated with MITRE ATT&CK techniques and validated against historical incidents. Results: Our analysis reveals a 150% rise in incidents, with OT compromise identified as the paramount threat (98/100 risk score). Ports in Poland and Taiwan face the …
The Performance Of Artificial Intelligence In Lesson Plans, Meghan Mezzacapo
The Performance Of Artificial Intelligence In Lesson Plans, Meghan Mezzacapo
Williams Honors College, Honors Research Projects
As a future teacher, I have recently observed the rapid growth of Artificial Intelligence (AI) in education. Many of the classes in my teacher education program have encouraged me to use AI as a tool for creating lesson plans. In schools, I have noticed an increased expectation from administrators that teachers use AI in the classroom. After experimenting with various Artificial Intelligence generators, I became interested in whether these tools could create a better lesson plan than myself. Determining AI’s capability may benefit teachers by allowing them to spend less time on creating lesson plans and more time on other …
Enhancing The Accuracy Of Image Classification For Degenerative Brain Diseases With Cnn Ensemble Models Using Mel-Spectrograms, Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim
Enhancing The Accuracy Of Image Classification For Degenerative Brain Diseases With Cnn Ensemble Models Using Mel-Spectrograms, Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim
Mathematics & Statistics Faculty Publications
Alzheimer’s disease (AD) and Parkinson’s disease (PD) are prevalent neurodegenerative disorders among the elderly, leading to cognitive decline and motor impairments. As the population ages, the prevalence of these neurodegenerative disorders is increasing, providing motivation for active research in this area. However, most studies are conducted using brain imaging, with relatively few studies utilizing voice data. Using voice data offers advantages in accessibility compared to brain imaging analysis. This study introduces a novel ensemble-based classification model that utilizes Mel spectrograms and Convolutional Neural Networks (CNNs) to distinguish between healthy individuals (NM), AD, and PD patients. A total of 700 voice …
Artificial Intelligence In Society: Transformations And Ethical Paradigm, Yashoda Urmilla Itwaru
Artificial Intelligence In Society: Transformations And Ethical Paradigm, Yashoda Urmilla Itwaru
Selected Full-Text Master Theses 2021-
The recent advancement and adoption of AI (Artificial Intelligence) make it vital to study the effects it has on individuals and communities. Adopting AI into daily life changes interactions such as the decision-making process and task performance. AI algorithms can shape a user’s online experiences, influence their preferences, beliefs, and behavior. However, people raised concerns regarding privacy, autonomy, and manipulation. For these reasons, debates regarding the ethical aspects of AI arose.
AI provides society with more tools to complete tasks. AI can automate data intensive jobs and physical tasks. This brings a sense of job insecurity, which affects the mental …
Insects, Ai Systems, And The Future Of Legal Personhood, Jeff Sebo
Insects, Ai Systems, And The Future Of Legal Personhood, Jeff Sebo
Animal Law Review
This Article makes a case for insect and AI legal personhood. Humans share the world not only with large animals like chimpanzees and elephants but also with small animals like ants and bees. In the future, we might also share the world with sentient or otherwise morally significant AI systems. These realities raise questions about what kind of legal status insects, AI systems, and other nonhumans should have in the future. At present, debates about legal personhood mostly exclude these kinds of individuals. However, I argue that our current framework for assessing legal personhood, coupled with our current framework for …
The Integration Of Big Data In Fintech: Review Of Enhancing Financial Services Through Advanced Technologies, Soudeh Pazouki, Mohammad B. Jamshidi, Mirarmia Jalali, Arya Tafreshi
The Integration Of Big Data In Fintech: Review Of Enhancing Financial Services Through Advanced Technologies, Soudeh Pazouki, Mohammad B. Jamshidi, Mirarmia Jalali, Arya Tafreshi
Management Faculty Publications
Big data analytics is revolutionizing the FinTech industry, offering new opportunities for real-time decision-making, personalized financial services, and improved risk management. By leveraging advanced technologies like machine learning and artificial intelligence, financial institutions can efficiently detect fraud, predict market trends, and create innovative solutions tailored to customer needs. Big data also plays a critical role in promoting financial inclusion through alternative credit scoring models, providing access to credit for underserved populations and fostering broader participation in the financial system.
However, the integration of big data into FinTech is not without its challenges. Issues such as data privacy concerns, regulatory complexities, …
Artificial Intelligence In Radiology, Olivia Sweeney
Artificial Intelligence In Radiology, Olivia Sweeney
Theses, Dissertations and Capstones
Introduction: Artificial intelligence (AI) has increasingly transformed radiologic practice by improving diagnostic accuracy, streamlining workflows, and reducing interpretation errors. As AI integration has expanded across imaging modalities, questions have emerged regarding its effectiveness compared to traditional radiologist-only interpretation.
Purpose of Study: The purpose of this study has been to evaluate the impact of AI-assisted radiology on diagnostic accuracy, efficiency, and error reduction, while also assessing clinician perceptions of AI as a collaborative tool in imaging analysis.
Methodology: This qualitative study has used a systematic review of peer-reviewed literature published between 2015 and 2025, following PRISMA guidelines, combined with an interview …
Sam Altman, Openai, And The Importance Of Corporate Governance, Lawrence J. Trautman, Larry D. Foster Ii
Sam Altman, Openai, And The Importance Of Corporate Governance, Lawrence J. Trautman, Larry D. Foster Ii
Journal of Law, Technology, & the Internet
The sudden firing of CEO Sam Altman by OpenAI’s three independent directors highlights concerns about whether a leading AI company, susceptible to internal conflict and unclear accusations, can be trusted to develop a technology with far-reaching consequences for billions of people.
This paper examines how OpenAI’s board of directors terminated CEO Sam Altman’s employment, a decision that risked hundreds of highly skilled employees walking out the door, disrupted billions of dollars in value, and jeopardized critical knowledge of this important technology. It is hoped that corporate directors—whether at for-profit and non-profit companies—along with venture capitalists, technologists, and government regulators can …
Navigating Copyright In Ai-Enhanced Game Design: Legal Challenges In Multimodal And Dynamic Content Creation, Andrew Begemann, James Hutson
Navigating Copyright In Ai-Enhanced Game Design: Legal Challenges In Multimodal And Dynamic Content Creation, Andrew Begemann, James Hutson
Faculty Scholarship
The integration of artificial intelligence (AI) in video game design has transformed traditional workflows, allowing for the generation of text, images, music, videos, and code at unprecedented scales. However, this advancement presents complex challenges for copyright law, traditionally rooted in human originality and authorship. This article examines recent case law that underscores the evolving legal landscape, exploring landmark cases such as Zarya of the Dawn and Andersen v. Stability AI. These cases reveal the tensions between AI-generated outputs and copyright eligibility, especially in the dynamic, multimodal compositions inherent to video games. The review analyzes how various AI tools are employed …
The Adoption Of Ai In Zimbabwe’S Newsrooms: A Case Of Zimpapers And Alpha Media Holdings, Muchemwa Silence Mugadzaweta
The Adoption Of Ai In Zimbabwe’S Newsrooms: A Case Of Zimpapers And Alpha Media Holdings, Muchemwa Silence Mugadzaweta
Master of Arts in Digital Journalism
Artificial Intelligence (AI) has changed the face of journalism in many ways. Newsrooms across the world are deploying AI in various aspects of news gathering distribution and creation. Many newsrooms are also at different stages when it comes to AI adoption. The general objective of this study was to examine the adoption of AI in two media houses in Zimbabwe: Zimpapers and Alpha Media Holdings (AMH), from newsroom operations and insights from journalists and editors to understand their perception and views on the future of journalism in the wake of AI technologies as well as documenting the status thereof. This …
Middle School Teachers’ Integration Of Artificial Intelligence Tools And Its Impact On Learning Outcomes In A Suburban School District, Donica Thompson-Chan
Middle School Teachers’ Integration Of Artificial Intelligence Tools And Its Impact On Learning Outcomes In A Suburban School District, Donica Thompson-Chan
Selected Full Text Dissertations, 2011-
Grounded in the Technology Acceptance Model (TAM), this study examined middle school teachers’ adoption of artificial intelligence (AI) tools, emphasizing how perceptions, instructional support, and integration strategies shape classroom use. The sample comprised 56 teachers across grades 6–8, representing multiple subject areas. Quantitative analyses revealed notable trends by teaching experience and subject specialization. Teachers with 0–5 years of experience reported the highest mean AI use scores, while those with more than 16 years of experience reported the lowest. Subject-specific differences were also observed, with mathematics teachers demonstrating the most favorable perceptions of AI tools and English teachers reporting the least …
Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu
Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu
Psychology Faculty Publications
Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …
Predicting Human Steering From Optic Flow Using Deep Convolutional Neural Networks, Katie E. Bernard
Predicting Human Steering From Optic Flow Using Deep Convolutional Neural Networks, Katie E. Bernard
Honors Theses
Human driving is a complex visuomotor task and the specific visual clues that guide it remain under investigation. While prior research has emphasized gaze-based strategies such as the Tangent Point and Future Path hypotheses, recent evidence highlights the potential role of optic flow, the visual motion pattern perceived during self-movement, as critical to steering ability. This thesis explores whether raw optic flow alone can support accurate predictions of human steering behavior. We trained a convolutional neural network to map optic flow vector fields to steering angles in a virtual reality driving simulation. The dataset, collected by Giguere et al., included …
Automating International Human Rights Adjudication, Veronika Fikfak, Laurence R. Helfer
Automating International Human Rights Adjudication, Veronika Fikfak, Laurence R. Helfer
Michigan Journal of International Law
International human rights courts and treaty bodies are increasingly turning to automated decision-making (“ADM”) technologies to expedite and enhance their review of individual complaints. These tribunals have yet to consider many of the legal, normative, and practical issues raised by the use of different types of automation technologies for these purposes. This article offers a comprehensive and balanced assessment of the benefits and challenges of introducing ADM into international human rights adjudication. We argue in favor of using ADM to digitize documents and for internal case management purposes and to make straightforward recommendations regarding registration, inadmissibility, and the calculation of …
Why Ai Monitoring Faces Resistance And What Healthcare Organizations Can Do About It: An Emotion-Based Perspective, Karl Werder, Lan Cao, Eun Hee Park, Balasubramaniam Ramesh
Why Ai Monitoring Faces Resistance And What Healthcare Organizations Can Do About It: An Emotion-Based Perspective, Karl Werder, Lan Cao, Eun Hee Park, Balasubramaniam Ramesh
Information Technology & Decision Sciences Faculty Publications
Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients' rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce …
Do Ais Dream Of Electric Boards?, Robert J. Rhee
Do Ais Dream Of Electric Boards?, Robert J. Rhee
UF Law Faculty Publications
When artificial intelligence (“AI”) acquires self-awareness, agency, and unique intelligence, it will attain ontological personhood. Management of firms by AI would be technologically and economically feasible. The law could confer AI with the status of legal personhood, as it did with the personhood of traditional business firms in the past, thus dispensing with the need for inserting AI as property within the legal boundary of a firm. As a separate and distinct entity, AI could function independently as a manager in the way that legal or natural persons do today: i.e., AI as director, officer, partner, member, or manager. Such …
A Vision Transformer Based Assistive System For Dermatological Diagnosis In Systemic Lupus Erythematosus, Syeda Lamima Farhat
A Vision Transformer Based Assistive System For Dermatological Diagnosis In Systemic Lupus Erythematosus, Syeda Lamima Farhat
All Graduate Theses, Dissertations, and Other Capstone Projects
Systemic Lupus Erythematosus (SLE) is a complex and often underdiagnosed autoimmune disease that affects multiple organs and presents with a wide range of symptoms-ranging from fatigue and joint pain to life-threatening organ damage. One of its most visible and diagnostically significant indicators is the Butterfly Malar Rash (BMR), a distinctive facial rash that often resembles other common dermatological conditions like rosacea, acne, eczema, and fifth disease. This overlap can lead to misdiagnosis or delayed detection, especially in busy clinical environments. To assist dermatologists in distinguishing BMR from similar facial rashes, this study explores the development of an AI-powered image classification …
A Personal Interview With William Patry: His Thoughts On Music, Ai, And Copyright
A Personal Interview With William Patry: His Thoughts On Music, Ai, And Copyright
IP Theory
No abstract provided.