AI Medical Compendium

A simple approach for biometrics: Finger-knuckle prints recognition based on a Sobel filter and similarity measures

arXiv May 17, 2026

The objective of this work is to propose a novel methodology for the finger knuckle print recognition, which is essentially a digital photo of the finger-knuckle region. We have employed very simple concepts of visual computing such as a filter based... read more

Computer Vision and Pattern Recognition

Attention-Guided Fusion of 1D and 2D CNNs for Robust ECG-Based Biometric Recognition

arXiv May 17, 2026

Electrocardiogram (ECG)-based biometric recognition has emerged as a promising solution for secure authentication and liveness detection. However, most existing methods rely on unimodal deep learning architectures that independently process either on... read more

Computer Vision and Pattern Recognition cs.AI cs.CR eess.SP eess.SY

Artificial intelligence-based decision support in simulated free flap Re-exploration for head and neck reconstruction. A case-based comparative study.

JPRAS open May 16, 2026

Free flap compromise after head and neck reconstruction requires rapid recognition and structured escalation. Large language models have shown potential for text-based clinical support, but their alignment with microsurgical decision-making in flap c... read more

National-scale prediction of arsenic, fluoride and its co-occurrence in groundwater of Mexico: Implications for drinking-water.

Journal of hazardous materials May 16, 2026

Arsenic (As) and fluoride (F-) in groundwater pose significant health risks and frequently co-occur in arid and semi-arid settings. We assembled a dataset comprising 3403 As measurements and 2084 F- measurements for Mexico (44% and 24% above the WHO ... read more

Machine Learning for Revision Joint Arthroplasty: A Systematic Review of Distinct Challenges, Current Performance, and Clinical Readiness.

Arthroplasty today May 16, 2026

BACKGROUND: Given the high complication rates and economic burden of revision total joint arthroplasty, machine learning (ML) models may offer a tool to improve outcomes. This study aims to review the application of ML for predicting outcomes followi... read more

A portable source-informed machine learning framework for predicting heavy metals in legacy smelting sites with strong spatial heterogeneity.

Journal of hazardous materials May 16, 2026

Legacy smelting sites often exhibit strong point-source control, highly right-skewed concentration distributions, and pronounced vertical stratification, which together challenge reliable spatial prediction of heavy metals (HMs) from limited borehole... read more

Intraoperative neurophysiological monitoring (IONM) in neurosurgery: A critical appraisal of established practices, ongoing controversies, and future trajectories.

Journal of anesthesia and translational medicine May 16, 2026

Intraoperative neurophysiological monitoring (IONM) has evolved from a novel technique into an evidence-based standard treatment method for high-risk neurosurgical and spinal surgeries. Its effectiveness is based on two interrelated pillars: optimize... read more

Quantum-enhanced federated blockchain for privacy-preserving cardiovascular intelligence.

Scientific reports May 16, 2026

Cardio-Vascular Diseases (CvDs) persist as a significant mortality reason worldwide, which requires advanced risk categorization technologies that can offer custom medicine while protecting patient information. Present healthcare approaches must over... read more

Integrated single-cell and bulk transcriptomic analyses unveil a necroptosis-related prognostic model and its association with tumor microenvironment remodeling in gastric cancer.

Discover oncology May 16, 2026

BACKGROUND: Necroptosis has emerged as a critical regulator in tumor progression and therapeutic response, yet its prognostic significance and influence on the tumor microenvironment (TME) in gastric cancer (GC) remain poorly characterized. Therefore... read more

Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis.

BMC medical informatics and decision making May 16, 2026

PURPOSE: Silicosis, the most dangerous and common lung illness associated with breathing in mineral dust, is a significant health concern. Although Respiratory Oscillometry and electrical models are powerful methods to evaluate the respiratory system... read more

Artificial Intelligence Medical Compendium