Clinical Trials

Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.

Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represen...

Graph Embedded Ensemble Deep Randomized Network for Diagnosis of Alzheimer's Disease.

Randomized shallow/deep neural networks with closed form solution avoid the shortcomings that exist ...

AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases.

Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalco...

Predicting Metformin Efficacy in Improving Insulin Sensitivity Among Women With Polycystic Ovary Syndrome and Insulin Resistance: A Machine Learning Study.

OBJECTIVE: Metformin is clinically effective in treating polycystic ovary syndrome (PCOS) with insul...

Improving the quality of Persian clinical text with a novel spelling correction system.

BACKGROUND: The accuracy of spelling in Electronic Health Records (EHRs) is a critical factor for ef...

Preoperative prediction of rectal Cancer staging combining MRI deep transfer learning, radiomics features, and clinical factors: accurate differentiation from stage T2 to T3.

BACKGROUND: This study evaluates the efficacy of integrating MRI deep transfer learning, radiomic si...

Robotic-Enhanced Prosthetic Liners for Vibration Therapy: Reducing Phantom Limb Pain in Transfemoral Amputees.

Phantom limb pain, a common challenge for amputees, lacks effective treatment options. Vibration the...

Artificial intelligence for surgical safety during laparoscopic gastrectomy for gastric cancer: Indication of anatomical landmarks related to postoperative pancreatic fistula using deep learning.

BACKGROUND: Postoperative pancreatic fistula (POPF) is a critical complication of laparoscopic gastr...

Deep learning is necessary for safety regulation in predicting malnutrition in gastric cancer patients.

CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture.

Driver monitoring systems (DMS) are crucial in autonomous driving systems (ADS) when users are conce...

Enhancing Postmarketing Surveillance of Medical Products With Large Language Models.

IMPORTANCE: The Sentinel System is a key component of the US Food and Drug Administration (FDA) post...

Early predictive values of clinical assessments for ARDS mortality: a machine-learning approach.

Acute respiratory distress syndrome (ARDS) is a devastating critical care syndrome with significant ...

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalitie...

Development of a CT-Based comprehensive model combining clinical, radiomics with deep learning for differentiating pulmonary metastases from noncalcified pulmonary hamartomas: a retrospective cohort study.

BACKGROUND: Clinical differentiation between pulmonary metastases and noncalcified pulmonary hamarto...

The artificial intelligence advantage: Supercharging exploratory data analysis.

Explorative data analysis (EDA) is a critical step in scientific projects, aiming to uncover valuabl...

Radiographical diagnostic competences of dental students using various feedback methods and integrating an artificial intelligence application-A randomized clinical trial.

INTRODUCTION: Radiographic diagnostic competences are a primary focus of dental education. This stud...

Predicting the severity of mood and neuropsychiatric symptoms from digital biomarkers using wearable physiological data and deep learning.

Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild cognitive imp...

Modeling the Impact of Ergonomic Interventions and Occupational Factors on Work-Related Musculoskeletal Disorders in the Neck of Office Workers with Machine Learning Methods.

BACKGROUND: Modeling with methods based on machine learning (ML) and artificial intelligence can hel...

Ultrasound Image Temperature Monitoring Based on a Temporal-Informed Neural Network.

Real-time and accurate temperature monitoring during microwave hyperthermia (MH) remains a critical ...

The effect of laparoscopic pneumoperitoneum on patient's respiratory variation of inferior vena cava and stroke volume index: A randomized controlled study.

BACKGROUND: The establishment of pneumoperitoneum has impacts on patient's cardiovascular function. ...

Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric MRI: A Review on Clinical Applications and Future Outlooks.

This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multi...