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Machine Learning Models for Predicting 24-Hour Intraocular Pressure Changes: A Comparative Study.
Medical science monitor : international medical journal of experimental and clinical research
Dec 3, 2024
BACKGROUND Predicting 24-hour intraocular pressure (IOP) fluctuations is crucial for enhancing glaucoma management. Traditional methods of measuring 24-hour IOP fluctuations are complex and present certain limitations. The present study leverages mac...
Integrating omics data and machine learning techniques for precision detection of oral squamous cell carcinoma: evaluating single biomarkers.
Frontiers in immunology
Dec 3, 2024
INTRODUCTION: Early detection of oral squamous cell carcinoma (OSCC) is critical for improving clinical outcomes. Precision diagnostics integrating metabolomics and machine learning offer promising non-invasive solutions for identifying tumor-derived...
Gender bias in text-to-image generative artificial intelligence depiction of Australian paramedics and first responders.
Australasian emergency care
Dec 2, 2024
INTRODUCTION: In Australia, almost 50 % of paramedics are female yet they remain under-represented in stereotypical depictions of the profession. The potentially transformative value of generative artificial intelligence (AI) may be limited by stereo...
Machine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer Ability in Spina Bifida.
Archives of physical medicine and rehabilitation
Dec 2, 2024
OBJECTIVE: To determine which statistical techniques enhance our ability to predict ambulation and transfer ability in people with spina bifida (SB).
AI-Based Evaluation of Prostate MR Imaging at a Modern Low-field 0.55 T Scanner Compared to 3 T in a Screening Cohort.
Academic radiology
Dec 2, 2024
PURPOSE: To evaluate the effect of lower field strength on quantitative apparent-diffusion-coefficient (ADC) values, contrast of the T2-weighted MR images and the performance of an AI-based segmentation.
Prediction of Medication-Related Osteonecrosis of the Jaw in Patients Receiving Antiresorptive Therapy Using Machine Learning Models.
Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
Dec 2, 2024
BACKGROUND: Medication-related osteonecrosis of the jaw (MRONJ) is a serious complication associated with the use of antiresorptive agents, impacting patient quality of life and treatment outcomes. Predictive modeling may aid in a better understandin...
Predicting high-flow arteriovenous fistulas and cardiac outcomes in hemodialysis patients.
Journal of vascular surgery
Dec 2, 2024
BACKGROUND: Heart failure is common in patients receiving hemodialysis. A high-flow arteriovenous fistula (AVF) may represent a modifiable risk factor for heart failure and death. Currently, no tools exist to assess the risk of developing a high-flow...
Predicting chemotherapy responsiveness in gastric cancer through machine learning analysis of genome, immune, and neutrophil signatures.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Dec 2, 2024
BACKGROUND: Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-related mortality worldwide. This study was initiated to address the variability in patient responses to combination chemotherapy, highlighting the nee...
Self-supervised neural network for Patlak-based parametric imaging in dynamic [F]FDG total-body PET.
European journal of nuclear medicine and molecular imaging
Dec 2, 2024
PURPOSE: The objective of this study is to generate reliable K parametric images from a shortened [F]FDG total-body PET for clinical applications using a self-supervised neural network algorithm.
Multitask learning for automatic detection of meniscal injury on 3D knee MRI.
Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Dec 2, 2024
Magnetic resonance imaging (MRI) of the knee is the recommended diagnostic method before invasive arthroscopy surgery. Nevertheless, interpreting knee MRI scans is a time-consuming process that is vulnerable to inaccuracies and inconsistencies. We pr...
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