Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1177/10398562241280348 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
OpenAI's Sora and Google's Veo 2 in Action: A Narrative Review of Artificial Intelligence-driven Video Generation Models Transforming Healthcare.
Cureus
January 2025
Otolaryngology-Head and Neck Surgery, College of Medicine, King Saud University, Riyadh, SAU.
The rapid evolution of generative artificial intelligence (AI) has introduced transformative technologies across various domains, with text-to-video (T2V) generation models emerging as transformative innovations in the field. This narrative review explores the potential of T2V AI generation models used in healthcare, focusing on their applications, challenges, and future directions. Advanced T2V platforms, such as Sora Turbo (OpenAI, Inc.
View Article and Find Full Text PDFdeep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities.
J Chem Inf Model
January 2025
School of Information and Artificial Intelligence, Anhui Provincial Engineering Research Center for Beidou Precision Agriculture Information, Key Laboratory of Agricultural Sensors for Ministry of Agriculture and Rural Affairs, Anhui Agricultural University, Hefei, Anhui 230036, China.
Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As the problem of pathogen resistance caused by the misuse of antibiotics intensifies, the identification of AMPs as alternatives to antibiotics has become a hot topic. Accurately identifying AMPs using computational methods has been a key issue in the field of bioinformatics in recent years.
View Article and Find Full Text PDFDevelopment of 3D-printed conducting microneedle-based electrochemical point-of-care device for transdermal sensing of chlorpromazine.
J Mater Chem B
January 2025
Joint Department of Biomedical Engineering, University of North Carolina and North Carolina State University, Raleigh, NC 27695, USA.
Despite the various benefits of chlorpromazine, its misuse and overdose may lead to severe side effects, therefore, creating a user-friendly point-of-care device for monitoring the levels of chlorpromazine drug to manage the potential side effects and ensure the effective and safe use of the medication is highly desired. In this report, we have demonstrated a simple and scalable manufacturing process for the development of a 3D-printed conducting microneedle array-based electrochemical point-of-care device for the minimally invasive sensing of chlorpromazine. We used an inkjet printer to print the carbon and silver ink onto a customized 3D-printed ultrasharp microneedle array for the preparation of counter, working, and reference electrodes.
View Article and Find Full Text PDFThe doctor will polygraph you now.
Npj Health Syst
December 2024
Center for Interventional Oncology, Clinical Center, National Institutes of Health (NIH), Bethesda, MD USA.
Artificial intelligence (AI) methods have been proposed for the prediction of social behaviors that could be reasonably understood from patient-reported information. This raises novel ethical concerns about respect, privacy, and control over patient data. Ethical concerns surrounding clinical AI systems for social behavior verification can be divided into two main categories: (1) the potential for inaccuracies/biases within such systems, and (2) the impact on trust in patient-provider relationships with the introduction of automated AI systems for "fact-checking", particularly in cases where the data/models may contradict the patient.
View Article and Find Full Text PDFSurvey evidence on public support for AI safety oversight.
Sci Rep
December 2024
Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway.
A number of AI safety concerns are being increasingly discussed by experts, including misinformation, invasion of privacy, job displacement, and criminal misuse. Two exploratory studies conducted in Germany and Spain (combined n = 2864) provide evidence that the general public largely supports strict oversight over safety of commercial artificial intelligence research. Among the factors that are associated with preferences for strict oversight are age, anticipated job displacement, innovativeness, and risk, time and altruistic preferences.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!