Artificial intelligence-driven patient monitoring for adverse event detection in clinical trials DOI Open Access

Sai Bhargavi Vampana,

E. Jayanthi,

D. A. S. G. Mary

et al.

International Journal of Basic & Clinical Pharmacology, Journal Year: 2024, Volume and Issue: 13(4), P. 543 - 550

Published: June 25, 2024

Artificial intelligence (AI) keeps an eye on people in clinical studies to find out when bad things happen. This is a big way that AI changing healthcare. It goes into lot of detail about how has changed this field and stresses important it use complicated formulas, always keep things, follow the rules. These days, we have tools like deep learning frameworks, controlled unsupervised models, others help us faster more accurately. Tracking real time possible with early warning systems constant data analysis. helps make sure experiment done right puts safety being tested first. AI-driven tracking can only work honest reliable if they rules set by regulatory bodies such as FDA EMA. The fact ability change medical research today, benefits making accurate, makes its problems even important. report comes conclusion research, better teamwork, wider technologies are needed events over time.

Language: Английский

Artificial Intelligence Models and Tools for the Assessment of Drug–Herb Interactions DOI Creative Commons
Marios Spanakis, Eleftheria Tzamali, Georgios Tzedakis

et al.

Pharmaceuticals, Journal Year: 2025, Volume and Issue: 18(3), P. 282 - 282

Published: Feb. 20, 2025

Artificial intelligence (AI) has emerged as a powerful tool in medical sciences that is revolutionizing various fields of drug research. AI algorithms can analyze large-scale biological data and identify molecular targets pathways advancing pharmacological knowledge. An especially promising area the assessment interactions. The analysis large datasets, such drugs’ chemical structure, properties, pathways, known interaction patterns, provide mechanistic insights potential associations by integrating all this complex information returning risks associated with these In context, an where may prove valuable underlying mechanisms interactions natural products (i.e., herbs) are used dietary supplements. These pose challenging problem since they mixtures constituents diverse limited regarding their pharmacokinetic data. As use herbal supplements continues to grow, it becomes increasingly important understand between them conventional drugs adverse reactions. This review will discuss approaches how be exploited providing prediction herbs, exploitation experimental validation or clinical utilization.

Language: Английский

Citations

1
Strengthening Drug Safety and Public Health Surveillance in the United States: The Role of Artificial Intelligence in Pharmacovigilance DOI

Eguolo Ann Majekodunmi

Published: Jan. 1, 2025

Language: Английский

Citations

0
Enhancing risk management in hospitals: leveraging artificial intelligence for improved outcomes DOI Creative Commons

Ranieri Guerra

Italian Journal of Medicine, Journal Year: 2024, Volume and Issue: 18(2)

Published: April 15, 2024

In hospital settings, effective risk management is critical to ensuring patient safety, regulatory compliance, and operational effectiveness. Conventional approaches assessment mitigation frequently rely on manual procedures retroactive analysis, which might not be sufficient recognize respond new risks as they arise. This study examines how artificial intelligence (AI) technologies can improve in healthcare facilities, fortifying safety precautions guidelines while improving the standard of care overall. Hospitals proactively identify mitigate risks, optimize resource allocation, clinical outcomes by utilizing AI-driven predictive analytics, natural language processing, machine learning algorithms. The different applications AI are discussed this paper, along with opportunities, problems, suggestions for their use settings.

Language: Английский

Citations

3
Artificial intelligence-driven patient monitoring for adverse event detection in clinical trials DOI Open Access

Sai Bhargavi Vampana,

E. Jayanthi,

D. A. S. G. Mary

et al.

International Journal of Basic & Clinical Pharmacology, Journal Year: 2024, Volume and Issue: 13(4), P. 543 - 550

Published: June 25, 2024

Artificial intelligence (AI) keeps an eye on people in clinical studies to find out when bad things happen. This is a big way that AI changing healthcare. It goes into lot of detail about how has changed this field and stresses important it use complicated formulas, always keep things, follow the rules. These days, we have tools like deep learning frameworks, controlled unsupervised models, others help us faster more accurately. Tracking real time possible with early warning systems constant data analysis. helps make sure experiment done right puts safety being tested first. AI-driven tracking can only work honest reliable if they rules set by regulatory bodies such as FDA EMA. The fact ability change medical research today, benefits making accurate, makes its problems even important. report comes conclusion research, better teamwork, wider technologies are needed events over time.

Language: Английский

Citations

1