-
The Utopia of Artificial Intelligence in Medicine
In previous posts, I’ve discussed various breakthroughs and tools in artificial intelligence that are helping transform the world of medical science and healthcare. Today, I want to dive into a concept that, when executed correctly, could revolutionize this field and unleash the full potential of AI. Large Language Models It hasn’t been long since large…
-
Evaluating AI Models: Decision Curve Analysis (DCA)
Today, we have a variety of tools to evaluate the performance of AI models. From basic metrics like accuracy and AUC to more complex ones like calibration plots and precision-recall curves, each offers unique insights. However, some of these metrics better convey the information clinicians find most relevant, helping them quickly decide whether a model…
-
AI-Powered Survival Prediction in Lung Cancer Using PET/CT Imaging
Published in: Journal of Nuclear Medicine (2024) Cited by: 1 Breakthrough: This study evaluates semi-supervised machine learning approaches for predicting lung cancer survival outcomes, integrating PET/CT imaging and clinical features.
-
PerPsych: Open-Source iPadOS Software for Neuropsychological Assessments
Published in: MethodsX (2024)Cited by: 2 Breakthrough:NAIRG introduces PerPsych, an open-source, tablet-based tool for assessing time perception and cognitive function. Key Findings:iPad-based assessment makes neuropsychological testing more accessible.PerPsych enhances real-time cognitive data collection.Ideal for clinical and research applications in neuroscience. Impact:This software enables widespread, cost-effective neuropsychological assessments, benefiting clinicians, researchers, and educators. Read More: [Insert…
-
Differentiating High-Grade Glioma vs. Brain Metastases
Published in: Journal of Magnetic Resonance Imaging (2024)Cited by: 2 Breakthrough:This study leverages cerebral perfusion imaging and AI to differentiate high-grade gliomas from metastatic brain tumors, improving diagnostic accuracy. Key Findings:AI models improve tumor classification in brain imaging.Machine learning integrates cerebral blood volume (CBV) and cerebral blood flow (CBF) data.AI enhances non-invasive diagnosis, reducing unnecessary…
-
AI-Driven Biomarker Discovery for Cognitive Decline in Parkinson’s Disease
Published in: Plos One (2024)Cited by: 2 Breakthrough:NAIRG researchers introduce an AI-powered biomarker discovery system to predict cognitive impairment within five years in Parkinson’s patients. Key Findings:Machine learning enhances predictive accuracy for cognitive decline.DAT SPECT imaging features serve as early biomarkers.AI models outperform traditional cognitive assessment scales. Impact:This study enhances early intervention strategies, helping physicians…
-
AI Predicts Lung Cancer Outcomes with Hybrid Machine Learning
Published in: Journal of Nuclear MedicineCited by: 4 (Since 2023) Breakthrough:NAIRG’s latest AI-driven study combines Tensor Deep Learning and Radiomics to predict lung cancer survival rates with unprecedented accuracy. Key Findings:Hybrid AI models improve lung cancer prognosis predictions.Deep radiomics features enhance tumor characterization.Fusion of PET-CT imaging improves survival outcome analysis. Impact:This research supports the clinical…
