AIMC Topic: Humans

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Automated Drug Coding Using Artificial Intelligence: An Evaluation of WHODrug Koda on Adverse Event Reports.

Drug safety
INTRODUCTION: Coding medicinal products described on adverse event (AE) reports to specific entries in standardised drug dictionaries, such as WHODrug Global, is a time-consuming step in case processing activities despite its potential for automation...

Artificial Intelligence-Based Pharmacovigilance in the Setting of Limited Resources.

Drug safety
With the rapid development of artificial intelligence (AI) technologies, and the large amount of pharmacovigilance-related data stored in an electronic manner, data-driven automatic methods need to be urgently applied to all aspects of pharmacovigila...

Applying Machine Learning in Distributed Data Networks for Pharmacoepidemiologic and Pharmacovigilance Studies: Opportunities, Challenges, and Considerations.

Drug safety
Increasing availability of electronic health databases capturing real-world experiences with medical products has garnered much interest in their use for pharmacoepidemiologic and pharmacovigilance studies. The traditional practice of having numerous...

Artificial Intelligence Based on Machine Learning in Pharmacovigilance: A Scoping Review.

Drug safety
INTRODUCTION: Artificial intelligence based on machine learning has made large advancements in many fields of science and medicine but its impact on pharmacovigilance is yet unclear.

Industry Perspective on Artificial Intelligence/Machine Learning in Pharmacovigilance.

Drug safety
TransCelerate reports on the results of 2019, 2020, and 2021 member company (MC) surveys on the use of intelligent automation in pharmacovigilance processes. MCs increased the number and extent of implementation of intelligent automation solutions th...

Artificial Intelligence in Pharmacovigilance: An Introduction to Terms, Concepts, Applications, and Limitations.

Drug safety
The tools of artificial intelligence (AI) have enormous potential to enhance activities in pharmacovigilance. Pharmacovigilance experts need not be AI experts, but they should know enough about AI to explore the possibilities of collaboration with th...

Artificial Intelligence and Machine Learning for Safe Medicines.

Drug safety
Authors' views on the role of artificial intelligence and machine learning in pharmacovigilance. (MP4  139807 kb).

Automated Detection Model Based on Deep Learning for Knee Joint Motion Injury due to Martial Arts.

Computational and mathematical methods in medicine
OBJECTIVE: Develop a set of knee joint martial arts injury monitoring models based on deep learning, train and evaluate the model's effectiveness.

The Application of Artificial Intelligence Technology in Art Teaching Taking Architectural Painting as an Example.

Computational intelligence and neuroscience
In the current era of technology, artificial intelligence has grown rapidly in such a way that it has established its presence in all fields. The purpose of artificial intelligence is to reduce human intervention and complete tasks with an enhanced r...

A Novel Deep Learning Network and Its Application for Pulmonary Nodule Segmentation.

Computational intelligence and neuroscience
Pulmonary nodules are the early manifestation of lung cancer, which appear as circular shadow of no more than 3 cm on the computed tomography (CT) image. Accurate segmentation of the contours of pulmonary nodules can help doctors improve the efficien...