AI Medical Compendium Journal:
Artificial intelligence in medicine

Showing 11 to 20 of 596 articles

Fuzzy-DDI: A robust fuzzy logic query model for complex drug-drug interaction prediction.

Artificial intelligence in medicine
Drug-drug interactions (DDI) refer to the compound effects that occur when patients take multiple drugs simultaneously, which may reduce the drug efficacy and even harm the patient's health. Therefore, DDI prediction is significant for drug developme...

Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models.

Artificial intelligence in medicine
A recent analysis of common stroke risk prediction models showed that performance differs between Black and White subgroups, and that applying standard machine learning methods does not reduce these disparities. There have been calls in the clinical ...

IdenBAT: Disentangled representation learning for identity-preserved brain age transformation.

Artificial intelligence in medicine
Brain age transformation aims to convert reference brain images into synthesized images that accurately reflect the age-specific features of a target age group. The primary objective of this task is to modify only the age-related attributes of the re...

Weakly supervised nuclei segmentation based on pseudo label correction and uncertainty denoising.

Artificial intelligence in medicine
Nuclei segmentation plays a vital role in computer-aided histopathology image analysis. Numerous fully supervised learning approaches exhibit amazing performance relying on pathological image with precisely annotations. Whereas, it is difficult and t...

Utilizing semantically enhanced self-supervised graph convolution and multi-head attention fusion for herb recommendation.

Artificial intelligence in medicine
Traditional Chinese herbal medicine has long been recognized as an effective natural therapy. Recently, the development of recommendation systems for herbs has garnered widespread academic attention, as these systems significantly impact the applicat...

Voice analysis in Parkinson's disease - a systematic literature review.

Artificial intelligence in medicine
BACKGROUND AND AIM: Parkinson's disease is a neurodegenerative disease. It is often diagnosed at an advanced stage, which can influence the control over the illness. Therefore, the possibility of diagnosing Parkinson's disease at an earlier stage, an...

Histopathology image classification based on semantic correlation clustering domain adaptation.

Artificial intelligence in medicine
Deep learning has been successfully applied to histopathology image classification tasks. However, the performance of deep models is data-driven, and the acquisition and annotation of pathological image samples are difficult, which limit the model's ...

Deep learning method for malaria parasite evaluation from microscopic blood smear.

Artificial intelligence in medicine
OBJECTIVE: Malaria remains a leading cause of global morbidity and mortality, responsible for approximately 5,97,000 deaths according to World Malaria Report 2024. The study aims to systematically review current methodologies for automated analysis o...

Comparing neural language models for medical concept representation and patient trajectory prediction.

Artificial intelligence in medicine
Effective representation of medical concepts is crucial for secondary analyses of electronic health records. Neural language models have shown promise in automatically deriving medical concept representations from clinical data. However, the comparat...

Deep learning based estimation of heart surface potentials.

Artificial intelligence in medicine
Electrocardiographic imaging (ECGI) aims to noninvasively estimate heart surface potentials starting from body surface potentials. This is classically based on geometric information on the torso and the heart from imaging, which complicates clinical ...