AIMC Topic: Sensitivity and Specificity
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Performance of deep learning for detection of chronic kidney disease from retinal fundus photographs: A systematic review and meta-analysis.
European journal of ophthalmology
Sep 6, 2023
OBJECTIVE: Deep learning has been used to detect chronic kidney disease (CKD) from retinal fundus photographs. We aim to evaluate the performance of deep learning for CKD detection.
Development and external validation of the multichannel deep learning model based on unenhanced CT for differentiating fat-poor angiomyolipoma from renal cell carcinoma: a two-center retrospective study.
Journal of cancer research and clinical oncology
Sep 6, 2023
PURPOSE: There are undetectable levels of fat in fat-poor angiomyolipoma. Thus, it is often misdiagnosed as renal cell carcinoma. We aimed to develop and evaluate a multichannel deep learning model for differentiating fat-poor angiomyolipoma (fp-AML)...
Machine Learning Algorithms to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis.
Neurocritical care
Sep 5, 2023
Delayed cerebral ischemia (DCI) is a common and severe complication after subarachnoid hemorrhage (SAH). Logistic regression (LR) is the primary method to predict DCI, but it has low accuracy. This study assessed whether other machine learning (ML) m...
Diabetic Retinopathy Screening Using Smartphone-Based Fundus Photography and Deep-Learning Artificial Intelligence in the Yucatan Peninsula: A Field Study.
Journal of diabetes science and technology
Aug 29, 2023
BACKGROUND: To compare the performance of Medios (offline) and EyeArt (online) artificial intelligence (AI) algorithms for detecting diabetic retinopathy (DR) on images captured using fundus-on-smartphone photography in a remote outreach field settin...
Deep learning algorithm for visual quality assessment of the spirograms.
Physiological measurement
Aug 29, 2023
. The quality of spirometry manoeuvres is crucial for correctly interpreting the values of spirometry parameters. A fundamental guideline for proper quality assessment is the American Thoracic Society and European Respiratory Society (ATS/ERS) Standa...
Use of artificial intelligence in triaging of chest radiographs to reduce radiologists' workload.
European radiology
Aug 24, 2023
OBJECTIVES: To evaluate whether deep learning-based detection algorithms (DLD)-based triaging can reduce outpatient chest radiograph interpretation workload while maintaining noninferior sensitivity.
Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function.
Cancer medicine
Aug 23, 2023
BACKGROUND: In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of toxicity and should therefore be monitored. We aimed to develop a machine learning model to identify those patients that need closer monitoring, enabl...
Non-invasive hemoglobin estimation from conjunctival images using deep learning.
Medical engineering & physics
Aug 22, 2023
Hemoglobin, a crucial protein found in erythrocytes, transports oxygen throughout the body. Deviations from optimal hemoglobin levels in the blood are linked to medical conditions, serving as diagnostic markers for certain diseases. The hemoglobin le...
Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study.
Journal of magnetic resonance imaging : JMRI
Aug 21, 2023
BACKGROUND: Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision-making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP p...
Stratifying High-Risk Thyroid Nodules Using a Novel Deep Learning System.
Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association
Aug 21, 2023
INTRODUCTION: The current ultrasound scan classification system for thyroid nodules is time-consuming, labor-intensive, and subjective. Artificial intelligence (AI) has been shown to increase the accuracy of predicting the malignancy rate of thyroid ...
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