Translating Potential Improvement in the Precision and Accuracy of Lung Nodule Measurements on Computed Tomography Scans by Software Derived from Artificial Intelligence into Impact on Clinical Practice—A Simulation Study

Information Science, Artificial Intelligence, Medicine, Respiratory System, Medical Imaging,
Artificial Intelligence   Simulation   Measurement Accuracy   Lung Nodule   Chest CT   Precision   Nodule Growth  

Potential Improvements in Lung Nodule Measurement Precision in Computed Tomography Using Artificial Intelligence Software and Its Impact on Clinical Practice - A Simulation Study Background Accurate measurement of lung nodules is crucial for the detection and management of lung cancer. Nodule size is the primary basis for risk classification in exi...

Clinical Validation of AI-Powered PD-L1 Tumor Proportion Score Interpretation for Predicting Immune Checkpoint Inhibitor Response in NSCLC

Information Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Oncology,
Artificial Intelligence   PD-L1   Tumor Proportion Score   Non-Small Cell Lung Cancer   Immune Checkpoint Inhibitors   Clinical Validation  

Clinical Validation of AI-based Interpretation of PD-L1 Tumor Proportion Score in Predicting Response to Immune Checkpoint Inhibitors in Non-small Cell Lung Cancer In the field of tumor treatment and diagnosis, the assessment of PD-L1 (Programmed Death-Ligand 1) Tumor Proportion Score (TPS) is a critical task, especially in predicting the response ...

AI-Powered Radiomics Algorithm Based on Slice Pooling for the Glioma Grading

AI-Powered Radiomics Algorithm Based on Slice Pooling for the Glioma Grading

Information Science, Artificial Intelligence, Medicine, Neurosurgery, Medical Imaging, Oncology,
Artificial Intelligence   Radiomics   Magnetic Resonance Imaging   Brain Tumors   Computer-Aided Diagnosis   Image Segmentation   Glioma Grading  

AI-Assisted Radiomics Algorithm for Glioma Grading Based on Slice Pooling Background Introduction Glioma is the most common and threatening tumor in the central nervous system, characterized by high incidence, high recurrence rates, high mortality, and low cure rates. The World Health Organization (WHO) classifies gliomas into four grades (I, II, I...

Tactile Perception: A Biomimetic Whisker-Based Method for Clinical Gastrointestinal Diseases Screening

Engineering, Mechanical Engineering, Information Science, Artificial Intelligence, Medicine, Gastroenterology, Medical Imaging, Life Sciences, Bioengineering,
Gastrointestinal Diseases   Biomimetic Whisker   Tactile Perception   Artificial Intelligence   Screening  

Clinical Gastrointestinal Disease Screening Based on the Bionic Artificial Tentacle Method Background Gastrointestinal diseases display a wide range of complex symptoms globally, such as diarrhea, gastrointestinal bleeding, malabsorption, malnutrition, and even neurological dysfunction. These diseases pose significant health challenges and socioeco...

Electronic Health Record Signatures Identify Undiagnosed Patients with Common Variable Immunodeficiency Disease

Electronic Health Record Signatures Identify Undiagnosed Patients with Common Variable Immunodeficiency Disease

Medicine, Rheumatology and Immunology, Environmental and Public Health,
Common Variable Immunodeficiency   Electronic Health Records   Machine Learning Algorithm   Immune System   Disease Diagnosis   Artificial Intelligence   Phenotype  

Utilizing Electronic Health Record Features to Identify Undiagnosed Patients with Common Subtype of Immunodeficiency Recently, Johnson and colleagues published a study titled “Electronic health record signatures identify undiagnosed patients with common variable immunodeficiency disease” in Science Translational Medicine. This research utilizes ele...

Development and Validation of Machine Learning Algorithms Based on Electrocardiograms for Cardiovascular Diagnoses at the Population Level

Information Science, Artificial Intelligence, Medicine, Cardiovascular System, Life Sciences, Biophysics,
Artificial Intelligence   Electrocardiogram   Cardiovascular Diseases   Deep Learning   Extreme Gradient Boosting  

Development and Validation of Large-Scale Machine Learning Algorithms for Cardiovascular Diagnosis Based on Electrocardiograms Introduction Cardiovascular diseases (CV) have long been a major source of global disease burden. Early diagnosis and intervention are crucial for reducing complications, healthcare utilization, and associated costs. Tradit...