Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
C Selvaraj, I Chandra, SK Singh - Molecular diversity, 2021 - Springer
The global spread of COVID-19 has raised the importance of pharmaceutical drug
development as intractable and hot research. Developing new drug molecules to overcome …
development as intractable and hot research. Developing new drug molecules to overcome …
Artificial intelligence: Machine learning approach for screening large database and drug discovery
PP Parvatikar, S Patil, K Khaparkhuntikar, S Patil… - Antiviral Research, 2023 - Elsevier
Recent research in drug discovery dealing with many faces difficulties, including
development of new drugs during disease outbreak and drug resistance due to rapidly …
development of new drugs during disease outbreak and drug resistance due to rapidly …
Thinking skills don't protect service workers from replacement by artificial intelligence
Despite the documented benefits of Artificial Intelligence (AI) to the service industry, the
service employees' fear of being replaced by AI continues to be a major concern as we …
service employees' fear of being replaced by AI continues to be a major concern as we …
Interventional Radiology ex-machina: Impact of Artificial Intelligence on practice
M Gurgitano, SA Angileri, GM Rodà, A Liguori… - La radiologia …, 2021 - Springer
Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process
data, understand its meaning and provide the desired outcome, continuously redefining its …
data, understand its meaning and provide the desired outcome, continuously redefining its …
[HTML][HTML] A bird's-eye view of deep learning in bioimage analysis
E Meijering - Computational and structural biotechnology journal, 2020 - Elsevier
Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …
solving data analysis problems in virtually all fields of science and engineering. Also in …
[HTML][HTML] Challenges in the development, deployment, and regulation of artificial intelligence in anatomic pathology
Significant advances in artificial intelligence (AI), deep learning, and other machine-learning
approaches have been made in recent years, with applications found in almost every …
approaches have been made in recent years, with applications found in almost every …
Challenges and opportunities of digital health in a post-COVID19 world
A Manteghinejad, SH Javanmard - Journal of Research in Medical …, 2021 - journals.lww.com
Digital health as a rapidly growing medical field relies comprehensively on human health
data. Conventionally, the collection of health data is mediated by officially diagnostic …
data. Conventionally, the collection of health data is mediated by officially diagnostic …
Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges
Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …
remarkable performance in providing medical professionals and patients with support for …
Barriers and enablers for artificial intelligence in dental diagnostics: a qualitative study
A Müller, SM Mertens, G Göstemeyer, J Krois… - Journal of Clinical …, 2021 - mdpi.com
The present study aimed to identify barriers and enablers for the implementation of artificial
intelligence (AI) in dental, specifically radiographic, diagnostics. Semi-structured phone …
intelligence (AI) in dental, specifically radiographic, diagnostics. Semi-structured phone …
Artificial intelligence in epilepsy
Background: The study of seizure patterns in electroencephalography (EEG) requires
several years of intensive training. In addition, inadequate training and human error may …
several years of intensive training. In addition, inadequate training and human error may …