This study presents data from a survey of 339 faculty predominantly in the sciences and social sciences about their use of artificial intelligence to improve their writing. The study helps its readers to answer questions such as: are faculty using AI to improve their writing? How many are doing so and in what academic fields is it most pronounced? Which applications are they using? How often are they using these applications and for what kinds of writing? What tasks in the writing process are they using AI for and what problems have they encountered? What advice can they give to their peers?Just a few of the many findings from this 49-page report are: More than 36% of faculty teaching at colleges and universities with fewer than 5,000 enrolled students FTE were using AI to aid their writing.Faculty teaching in medical schools submitted 19.5% of their writing projects to an artificial intelligence application for editing or other improvement.Younger respondents were far likelier than older ones to feel that AI was helping their writing. Data in the report was derived from a survey drawing 339 responses from faculty from 100 colleges and universities in the USA; it was conducted from November 2023 to February 2024. Data is broken out by variables related to the institutional affiliation of the survey participants (enrollment size, public/private status/ as well as personal characteristics such as age, gender, and academic field.

Those entrenched in academia often have daunting processes of formulating research questions, data collection, analysis, and scholarly paper composition. Artificial intelligence (AI) emerges as an invaluable ally, simplifying these processes and elevating the quality of scholarly output. Where the pursuit of knowledge meets the cutting edge of technology, Utilizing AI Tools in Academic Research Writing unfolds a transformative journey through the symbiotic relationship between AI and academic inquiry. It offers practical insights into the myriad ways AI can revolutionize academic pursuits. This book extends beyond theoretical discussions, delving into practical dimensions of AI integration, demonstrating how it facilitates topic identification, refines research design, empowers data analysis, and enriches literature reviews. Readers will explore AI's indispensable role in precise hypothesis development, enhancing the very foundation of academic inquiry. The book introduces AI-powered tools that streamline writing and editing, ensuring research papers meet the highest standards of clarity and correctness. Ethical considerations in AI-integrated research take center stage, emphasizing responsible and transparent practices. This book is ideal for doctoral candidates, master's students, undergraduates, or seasoned faculty members.

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Provides immediate help for anyone preparing a biomedical paper by givin specific advice on organizing the components of the paper, effective writing techniques, writing an effective results sections, documentation issues, sentence structure and much more. The new edition includes new examples from the current literature including many involving molecular biology, expanded exercises at the end of the book, revised explanations on linking key terms, transition clauses, uses of subheads, and emphases. If you plan to do any medical writing, read this book first and get an immediate advantage.

Today’s research scholars face the problem of how to effectively navigate the transformative impact of Artificial Intelligence (AI) while maintaining ethical integrity and scholarly rigor. AI technologies have permeated every aspect of scholarly inquiry, from information retrieval to research methodologies. As such, scholars grapple with the ethical implications, challenges, and opportunities presented by this technological revolution. Plagiarism, bias, and copyright issues in AI-assisted research threaten to undermine the integrity of academic scholarship. Navigating AI in Academic Libraries: Implications for Academic Research is presented as a groundbreaking solution to the complex challenges posed by AI integration in academia. This comprehensive volume serves as a guide for scholars seeking to navigate the intricacies of AI while upholding ethical standards and scholarly integrity. By addressing critical issues such as plagiarism detection, bias mitigation, and copyright concerns, the book equips scholars with the tools and strategies needed to harness the full potential of AI for academic inquiry.

Frontiers in Nutrition is delighted to launch the Rising stars in Nutrition and Food Science Technology 2022 article collection. This collection showcases the high-quality work of internationally recognized researchers in the early to mid-stages of their research careers. Recognizing the future leaders of Nutritional research is fundamental to safeguarding tomorrow's driving force in innovation. While future innovations in nutrition and food science technology are yet to be discovered, this Research Topic will give us a hint at whom to follow.