The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that led to the COVID-19 (Coronavirus Disease 2019) pandemic, has resulted in substantial overburdening of healthcare systems as well as an economic crisis on a global scale. This has in turn resulted in widespread efforts to identify suitable therapies to address this aggressive pathogen. Therapeutic antibody and vaccine development are being actively explored, and a phase I clinical trial of mRNA-1273 which is developed in collaboration between the National Institute of Allergy and Infectious Diseases and Moderna, Inc. is currently underway. Timelines for the broad deployment of a vaccine and antibody therapies have been estimated to be 12-18 months or longer. These are promising approaches that may lead to sustained efficacy in treating COVID-19. However, its emergence has also led to a large number of clinical trials evaluating drug combinations composed of repurposed therapies. As study results of these combinations continue to be evaluated, there is a need to move beyond traditional drug screening and repurposing by harnessing artificial intelligence (AI) to optimize combination therapy design. This may lead to the rapid identification of regimens that mediate unexpected and markedly enhanced treatment outcomes.
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http://dx.doi.org/10.1002/aisy.202000070 | DOI Listing |
J Med Internet Res
January 2025
Department of Cardiology, Yonsei University College of Medicine, Seoul, Republic of Korea.
Background: Efficient emergency patient transport systems, which are crucial for delivering timely medical care to individuals in critical situations, face certain challenges. To address this, CONNECT-AI (CONnected Network for EMS Comprehensive Technical-Support using Artificial Intelligence), a novel digital platform, was introduced. This artificial intelligence (AI)-based network provides comprehensive technical support for the real-time sharing of medical information at the prehospital stage.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Background: Individuals with hearing impairments may face hindrances in health care assistance, which may significantly impact the prognosis and the incidence of complications and iatrogenic events. Therefore, the development of automatic communication systems to assist the interaction between this population and health care workers is paramount.
Objective: This study aims to systematically review the evidence on communication systems using human-computer interaction techniques developed for deaf people who communicate through sign language that are already in use or proposed for use in health care contexts and have been tested with human users or videos of human users.
J Phys Chem Lett
January 2025
Key Laboratory of Atomic and Molecular Physics and Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China.
Research on memristive devices to seamlessly integrate and replicate the dynamic behaviors of biological synapses will illuminate the mechanisms underlying parallel processing and information storage in the human brain, thereby affording novel insights for the advancement of artificial intelligence. Here, an artificial electric synapse is demonstrated on a one-step Mo-selenized MoSe memristor, having not only long-term stable resistive switching characteristics (reset 0.51 ± 0.
View Article and Find Full Text PDFTransl Vis Sci Technol
January 2025
School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.
Purpose: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.
Methods: The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels.
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