Results 251 to 260 of about 221,929 (334)

Generation of Facial Drawings Using Generative Adversarial Networks

, 2019
Debabrata Datta, Abhradeep Dey, Adityam Ghosh, Rishabh Tiwari   +3 more
openalex   +1 more source

Advancing Food Safety Through Artificial Intelligence: A Detailed Review of Monitoring and Detection Technologies

Food Safety and Health, EarlyView.
Artificial intelligence (AI) is revolutionizing food safety by enabling rapid detection, real‐time monitoring, and enhanced traceability. This review highlights recent advances, applications, and future directions for AI‐driven technologies in safeguarding the global food supply.
Anju Kanicheril Ambikalekshmi, Poojitha Pushparaj, Elsa Cherian, Rosamma Rajan, Lakshmi Mohan   +4 more
wiley   +1 more source

Applications of generative adversarial networks in the diagnosis, prognosis, and treatment of ophthalmic diseases. [PDF]

Graefes Arch Clin Exp Ophthalmol
Doorly R, Ong J, Waisberg E, Sarker P, Zaman N, Tavakkoli A, Lee AG.   +6 more
europepmc   +1 more source

Application of Artificial Intelligence in Clinical Microbiology: From Research to Practice

iLABMED, EarlyView.
This paper reviews the application of AI in clinical microbiology practice at home and abroad, including rapid pathogen identification, accurate characterization of microbial resistance patterns, optimization of laboratory workflows, and public health interventions.
Ting Ding, Yi‐Wei Tang, Xiaoke Hao
wiley   +1 more source

AdvFaceGAN: a face dual-identity impersonation attack method based on generative adversarial networks. [PDF]

PeerJ Comput Sci
Huang H, Yang Y, Wang Y.
europepmc   +1 more source

Artificial Intelligence Revolutionizes Anti‐Infective Drug Discovery: From Target Identification to Lead Optimization

iMetaMed, EarlyView.
Artificial intelligence (AI) technology is revolutionizing antimicrobial drug development. In response to increasingly severe antimicrobial resistance challenges, AI can efficiently predict pathogen evolutionary trends, identify potential drug targets, and accelerate compound design and optimization, thereby significantly shortening the development ...
Kexin Li, Quan Yuan, Chang Qi, Ying Shi, Hong Yang, Anqi Lin, Shuofeng Yuan   +6 more
wiley   +1 more source

Thyroid disease classification using generative adversarial networks and Kolmogorov-Arnold network for three-class classification. [PDF]

BMC Med Inform Decis Mak
Topşir A, Güler F, Çetin E, Burak MF, Ağraz M.   +4 more
europepmc   +1 more source

Medical Data as a Key Asset in the Digital Health Era: A Framework for Challenges and Strategies

iMetaMed, EarlyView.
By conducting case studies and comparative analysis from a global perspective, this study develops the practical framework of Medical Data Element Ecosystem (MDEE)—one that facilitates MDEE construction by guiding actions, informing policy‐making, and enabling stakeholder engagement.
Jian Wang, Anqi Lin, Yedong Huang, Gezheng Li, Tianqi Chen, Chudi Sun, Weiye Qian, Shiqi Ren, Hank Z. H. Wong, Yanxi Ding, Lin Zhang   +10 more
wiley   +1 more source

Super-resolution of 3D medical images by generative adversarial networks with long and short-term memory and attention. [PDF]

Sci Rep
Zhang Q, Hang Y, Wu F, Wang S, Hong Y.
europepmc   +1 more source

TargetGen‐RNN model discovers novel antibiotic compound targeting drug‐resistant Staphylococcus aureus

Interdisciplinary Medicine, EarlyView.
TargetGen‐recurrent neural network (RNN), an advanced generative model, generated 28,708 unique and novel compounds, identifying SAK‐2970 as a potent antibiotic against drug‐resistant Staphylococcus aureus. Exhibiting strong biofilm inhibition, high therapeutic efficacy, and minimal systemic toxicity in vivo, SAK‐2970 highlights its safety and clinical
Shakeel Ahmad Khan, Adnan Shakoor, Sadia Kanwal   +2 more
wiley   +1 more source