Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 48,571 to 48,580 of 224,513 articles

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort.

Open heart
OBJECTIVE: Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk prediction models, such as the Framingham Cardiovascula... read more 

Automated Gating of CD34+ Cells in Cord Blood: Performance Evaluation of a Machine Learning-Based ISHAGE Protocol.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Precise quantification of cellular subsets is fundamental for qualifying grafts and supporting emerging therapies. CD34+ enumeration in cord blood using the ISHAGE protocol exemplifies the operator variability inherent to manual gating. We evaluated ... read more 

A comprehensive UK crop yield dataset incorporating satellite, weather, and soil type information.

Scientific data
Agricultural research increasingly relies on data-driven approaches for crop yield prediction that complement more established crop growth models, including machine learning techniques. However, these approaches rely on large training datasets. Here,... read more 

Combining multimodal fatigue fracture surface images for analysis with a CNN.

Scientific reports
This work uses three different modalities, namely SEM, BSE and scanning white light interference (SWLI) to image fatigue fracture surfaces of Ti-6Al-4V. Convolutional neural networks (CNNs) that were pre-trained on images of the natural world were us... read more 

Classification of rice plant diseases using efficient DenseNet121.

Scientific reports
Agriculture and global food security are critically dependent on accurate and timely identification of plant diseases and pests. Traditional approaches to disease identification rely heavily on visual inspection and expert knowledge, which frequently... read more 

Evaluation of cross-ethnic emotion recognition capabilities in multimodal large language models using the reading the mind in the eyes test.

Scientific reports
Accurate emotion recognition is a foundational component of social cognition, yet human biases can compromise its reliability. The emergent capabilities of multimodal large language models (MLLMs) offer a potential avenue for objective analysis, but ... read more