Latest AI and machine learning research in transplantation for healthcare professionals.
Large Language Models (LLMs) with hundreds of billions of parameters have exhibited human-like intelligence by learning from vast amounts of internet-scale data. However, the uninterpretability of large-scale neural networks raises concerns about the reliability of LLM. Studies have attempted to assess the psychometric properties of LLMs by borrowing concepts from human psychology to enhance their...
Maintaining optimal health and preventing diabetes-related complications require accurate and timely monitoring of blood glucose levels. In this context, the present study develops an affordable, reliable, and precise Point-of-Care (POC) diagnostic platform for glucose detection by integrating microfluidic and colorimetric principles. The system uses a custom-fabricated microfluidic chip that enab...
Tumorigenesis can be induced by diverse environmental carcinogens, with mercury (Hg)-a global pollutant that accumulates in humans throughout life, cr...
PURPOSE: Obesity is strongly associated with hepatocellular carcinoma (HCC), yet the molecular mechanisms linking them remain unclear. This study aime...
This paper introduces a strict AI-based framework of analysis of HRES in technical and economic dimensions to drive remote BTS.The proposed system del...
INTRODUCTION/AIMS: Myasthenia gravis (MG) is associated with thymic neoplasms. However, an increased prevalence of extrathymic neoplasms has also been...
PURPOSE: To map and synthesise current evidence on machine learning (ML) applications for anterior cruciate ligament (ACL) injury risk estimation, reh...
OCCUPATIONAL APPLICATIONSThis pilot study demonstrates the feasibility of using EEG-derived features to characterize behavioral reliance among enginee...
BACKGROUND: As unshaven hair transplantation grows in popularity, terminology has become inconsistent across publications and advertising. This create...
BACKGROUND: There is an increasing amount of evidence on microbiome-drug interactions in several clinical settings, including in immunocompromised pat...
OBJECTIVES: To evaluate and compare the trueness of four commercial AI-driven segmentation tools (Diagnocat, Relu, CephX, CoDiagnostiX) and one open-s...
Cancer remains a leading cause of global mortality, with early diagnosis being pivotal for improving treatment outcomes. Traditional tissue biopsy is ...
Fibrosis is a maladaptive pathophysiological process characterized by excessive deposition of extracellular matrix resulting from dysregulated tissue ...
INTRODUCTION: . Pharmacological treatment is the mainstay in the acute and long-term management of severe mental disorders such as major depressive di...
BACKGROUND: Vancomycin-resistant Enterococcus (VRE) infection is a life-threatening complication after liver transplantation (LT). This study aimed to...
The ubiquitous use of plastics in modern society is accompanied by the pervasive occurrence of plastic pollution. Of particular concern are nanoplasti...
In order to address the tracking accuracy degradation of the tank gun control system (TGCS) with inherent structural nonlinearity and feedback hystere...
Chimeric antigen receptor (CAR) T-cell therapy has achieved remarkable success in hematologic malignancies but continues to face significant barriers ...
Patient-based real-time quality control (PBRTQC) serves as a vital supplement to quality management in clinical laboratories. Its core principle is to...
OBJECTIVES: To evaluate the accuracy of CT-derived fat fraction (CDFF) software for quantifying hepatic steatosis at various radiation doses, using MR...