AIMC Topic: Artificial Intelligence

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Designing AI for mental health diagnosis: challenges from sub-Saharan African value-laden judgements on mental health disorders.

Journal of medical ethics
Recently clinicians have become more reliant on technologies such as artificial intelligence (AI) and machine learning (ML) for effective and accurate diagnosis and prognosis of diseases, especially mental health disorders. These remarks, however, ap...

Perspectives on the use of machine learning for ADME prediction at AstraZeneca.

Xenobiotica; the fate of foreign compounds in biological systems
A drug's pharmacokinetic (PK) profile will determine its dose and the frequency of administration as well as the likelihood of observing any adverse drug reactions.It is important to understand these PK properties as early as possible in the drug dis...

Through a computer monitor darkly: artificial intelligence in absorption, distribution, metabolism and excretion science.

Xenobiotica; the fate of foreign compounds in biological systems
Artificial Intelligence (AI) is poised or has already begun to influence absorption, distribution, metabolism and excretion (ADME) science. It is not in the area expected - that of superior modelling of ADME data to increase its predictive power. It ...

Artificial Intelligence in Chronic Obstructive Pulmonary Disease: Research Status, Trends, and Future Directions --A Bibliometric Analysis from 2009 to 2023.

International journal of chronic obstructive pulmonary disease
OBJECTIVE: A bibliometric analysis was conducted using VOSviewer and CiteSpace to examine studies published between 2009 and 2023 on the utilization of artificial intelligence (AI) in chronic obstructive pulmonary disease (COPD).

Artificial intelligence-based pulmonary embolism classification: Development and validation using real-world data.

PloS one
This paper presents an artificial intelligence-based classification model for the detection of pulmonary embolism in computed tomography angiography. The proposed model, developed from public data and validated on a large dataset from a tertiary hosp...