Artificial Intelligence Medical Compendium

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

Showing 941 to 950 of 160,728 articles

To What Extent Can Public Equity Indices Statistically Hedge Real Purchasing Power Loss in Compounded Structural Emerging-Market Crises? An Explainable ML-Based Assessment

arXiv Jul 17, 2025
This study investigates the extent to which local public equity indices can statistically hedge real purchasing power loss during compounded structural macro-financial collapses in emerging markets. We employ a non-linear multiplicative real return... read more 
Computational Engineering, Finance, and Science

An AI method to predict pregnancy loss by extracting biological indicators from embryo ultrasound recordings in early pregnancy.

Scientific reports Jul 17, 2025
B-ultrasound results are widely used in early pregnancy loss (EPL) prediction, but there are inevitable intra-observer and inter-observer errors in B-ultrasound results especially in early pregnancy, which lead to inconsistent assessment of embryonic... read more 
Humans Neural Networks, Computer Artificial Intelligence Pregnancy Female Adult Ultrasonography, Prenatal Pregnancy Trimester, First Abortion, Spontaneous Heart Rate, Fetal Gestational Age Crown-Rump Length

Adversarial attacks to image classification systems using evolutionary algorithms

arXiv Jul 17, 2025
Image classification currently faces significant security challenges due to adversarial attacks, which consist of intentional alterations designed to deceive classification models based on artificial intelligence. This article explores an approach ... read more 
Neural and Evolutionary Computing

Transcriptional modulation unique to vulnerable motor neurons predicts ALS across species and SOD1 mutations.

Genome research Jul 17, 2025
Amyotrophic lateral sclerosis (ALS) is characterized by the progressive loss of motor neurons (MNs) that innervate skeletal muscles. However, certain MN groups including ocular MNs, are relatively resilient. To reveal key drivers of resilience versus... read more 

MUPAX: Multidimensional Problem Agnostic eXplainable AI

arXiv Jul 17, 2025
Robust XAI techniques should ideally be simultaneously deterministic, model agnostic, and guaranteed to converge. We propose MULTIDIMENSIONAL PROBLEM AGNOSTIC EXPLAINABLE AI (MUPAX), a deterministic, model agnostic explainability technique, with gu... read more 
Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition

FSS-ULivR: a clinically-inspired few-shot segmentation framework for liver imaging using unified representations and attention mechanisms.

Journal of cancer research and clinical oncology Jul 17, 2025
Precise liver segmentation is critical for accurate diagnosis and effective treatment planning, serving as a foundation for medical image analysis. However, existing methods struggle with limited labeled data, poor generalizability, and insufficient ... read more 
Humans Algorithms Tomography, X-Ray Computed Liver Neoplasms Image Processing, Computer-Assisted Liver

The impact of artificial intelligence on green economy efficiency under integrated governance.

Scientific reports Jul 17, 2025
This study investigates the impact of Artificial Intelligence (AI) on Green Economic Efficiency (GEE) using panel data from 30 Chinese provinces spanning from 2011 to 2020. The empirical results demonstrate that AI significantly enhances GEE, with it... read more 

Knowledge-augmented Patient Network Embedding-based Dynamic Model Selection for Predictive Analysis of Pediatric Drug-induced Liver Injury.

IEEE transactions on bio-medical engineering Jul 17, 2025
OBJECTIVE: To address the challenges of developing machine learning frameworks for Electronic Health Records (EHRs)-based predictive tasks, such as the intricate occurrence mechanism of clinical events, patient diversity, and the inherent limitations... read more 

M4CEA: A Knowledge-guided Foundation Model for Childhood Epilepsy Analysis.

IEEE journal of biomedical and health informatics Jul 17, 2025
Existing electroencephalogram (EEG)-based deep learning models are mainly designed for single or several specific tasks in childhood epilepsy analysis, which limits the perceptual capabilities and generalisability of the model. Recently, Foundation M... read more 

Predicting liver metastasis in colorectal cancer patients using routine biochemical tests enhanced by machine learning.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Jul 17, 2025
BACKGROUND: Liver is the most common metastatic site in colorectal cancer. This study aims to evaluate the effectiveness of different machine learning (ML) models in predicting liver metastasis in CRC patients using routine biochemical tests. read more 
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