[HTML][HTML] Artificial intelligence and machine learning in pharmacological research: bridging the gap between data and drug discovery
Artificial intelligence (AI) has transformed pharmacological research through machine
learning, deep learning, and natural language processing. These advancements have …
learning, deep learning, and natural language processing. These advancements have …
A Systematic Review of Adversarial Machine Learning Attacks, Defensive Controls and Technologies
J Malik, R Muthalagu, PM Pawar - IEEE Access, 2024 - ieeexplore.ieee.org
Adversarial machine learning (AML) attacks have become a major concern for organizations
in recent years, as AI has become the industry's focal point and GenAI applications have …
in recent years, as AI has become the industry's focal point and GenAI applications have …
[PDF][PDF] Adversarial machine learning
Abstract This NIST Trustworthy and Responsible AI report develops a taxonomy of concepts
and defines terminology in the field of adversarial machine learning (AML). The taxonomy is …
and defines terminology in the field of adversarial machine learning (AML). The taxonomy is …
Privacy-enhancing technologies in biomedical data science
The rapidly growing scale and variety of biomedical data repositories raise important privacy
concerns. Conventional frameworks for collecting and sharing human subject data offer …
concerns. Conventional frameworks for collecting and sharing human subject data offer …
Use of generative AI in research: ethical considerations and emotional experiences
This study examines researchers' ethical concerns toward the deployment of GenAI in
research and their emotional responses. To acquire an in-depth understanding, we used …
research and their emotional responses. To acquire an in-depth understanding, we used …
Historical, philosophical and ethical roots of artificial intelligence
Artificial intelligence (AI) generally refers to the science of creating machines that carry out
tasks inspired by human intelligence, such as speech-image recognition, learning …
tasks inspired by human intelligence, such as speech-image recognition, learning …
[HTML][HTML] Practices and attitudes of Bavarian stakeholders regarding the secondary use of health data for research purposes during the COVID-19 pandemic: qualitative …
Background The COVID-19 pandemic is a threat to global health and requires collaborative
health research efforts across organizations and countries to address it. Although routinely …
health research efforts across organizations and countries to address it. Although routinely …
Multi-level ethical considerations of artificial intelligence health monitoring for people living with Parkinson's disease
Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope
that AI can enhance our health system's ability to care for people with chronic and …
that AI can enhance our health system's ability to care for people with chronic and …
Unlocking the potential of big data and AI in medicine: insights from biobanking
Big data and artificial intelligence are key elements in the medical field as they are expected
to improve accuracy and efficiency in diagnosis and treatment, particularly in identifying …
to improve accuracy and efficiency in diagnosis and treatment, particularly in identifying …
Artificial intelligent tools: evidence-mapping on the perceived positive effects on patient-care and confidentiality
NN Botha, EW Ansah, CE Segbedzi, VK Dumahasi… - BMC Digital Health, 2024 - Springer
Background Globally, healthcare systems have always contended with well-known and
seemingly intractable challenges like safety, quality, efficient and effective clinical and …
seemingly intractable challenges like safety, quality, efficient and effective clinical and …