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Implementation of Machine Learning Software on the Radiology Worklist Decreases Scan View Delay for the Detection of Intracranial Hemorrhage on CT

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Systematic Review of Artificial Intelligence for Abnormality Detection in High-volume Neuroimaging and Subgroup Meta-analysis for Intracranial Hemorrhage Detection

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Can Artificial Intelligence Reliably Report Chest X-Rays?: Radiologist Validation of an Algorithm trained on 2.3 Million X-RaysPreprint

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Automated Computer-Aided Detection and Classification of Intracranial Hemorrhage Using Ensemble Deep Learning Techniques

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BHSD: A 3D Multi-class Brain Hemorrhage Segmentation Dataset

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Segmentation of Intracranial Hemorrhage Using Semi-Supervised Multi-Task Attention-Based U-Net

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Pneumonia detection based on RSNA dataset and anchor-free deep learning detector

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Identifying Fatal Head Injuries on Postmortem Computed Tomography Using Convolutional Neural Network/Deep Learning: A Feasibility Study

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Alberta Stroke Program Early CT Score Calculation Using the Deep Learning-Based Brain Hemisphere Comparison Algorithm

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Artificial Intelligence in Neuroimaging: Clinical Applications

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A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations

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Leveraging physiology and artificial intelligence to deliver advancements in health care

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A Machine Learning Algorithm to Predict the Probability of (Occult) Posterior Malleolar Fractures Associated With Tibial Shaft Fractures to Guide “Malleolus First” Fixation

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Automatic Assessment of ASPECTS Using Diffusion-Weighted Imaging in Acute Ischemic Stroke Using Recurrent Residual Convolutional Neural Network

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Deep learning can predict survival directly from histology in clear cell renal cell carcinoma

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A review on artificial intelligence for the diagnosis of fractures in facial trauma imaging

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Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: a pilot study

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A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound

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CT-based deep learning model for predicting hospital discharge outcome in spontaneous intracerebral hemorrhage

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IILS: Intelligent imaging layout system for automatic imaging report standardization and intra-interdisciplinary clinical workflow optimization

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One-Shot Generative Adversarial Learning for MRI Segmentation of Craniomaxillofacial Bony Structures

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Deep Convolutional Neural Networks for Automatic Detection of Orbital Blowout Fractures

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Intracranial Hemorrhage Detection in CT Scans using Deep Learning

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Performance of an artificial intelligence tool with real-time clinical workflow integration – Detection of intracranial hemorrhage and pulmonary embolism

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Convolutional neural network performance compared to radiologists in detecting intracranial hemorrhage from brain computed tomography: A systematic review and meta-analysis

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Artificial Intelligence for Emerging Technology in Surgery: Systematic Review and Validation

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Identification of early invisible acute ischemic stroke in non-contrast computed tomography using two-stage deep-learning model

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Are All Deep Learning Architectures Alike for Point‐of‐Care Ultrasound?: Evidence From a Cardiac Image Classification Model Suggests Otherwise

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Automated Segmentation and Severity Analysis of Subdural Hematoma for Patients with Traumatic Brain Injuries

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Current State and Future Perspectives of Artificial Intelligence for Automated Coronary Angiography Imaging Analysis in Patients with Ischemic Heart Disease

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Prediction of preterm birth using artificial intelligence: a systematic review

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Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging

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Diagnostic Accuracy of Deep Learning for Intracranial Hemorrhage Detection in Non-Contrast Brain CT Scans: A Systematic Review and Meta-Analysis

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Development and validation of an abnormality-derived deep-learning diagnostic system for major respiratory diseases

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Early stage NSCLS patients’ prognostic prediction with multi-information using transformer and graph neural network model

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From the diagnosis of infectious keratitis to discriminating fungal subtypes; a deep learning-based study

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Deep learning-assisted detection and segmentation of intracranial hemorrhage in noncontrast computed tomography scans of acute stroke patients: a systematic review and meta-analysis

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Low-dose computed tomography perceptual image quality assessment

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A deep neural network for 12-lead electrocardiogram interpretation outperforms a conventional algorithm, and its physician overread, in the diagnosis of atrial fibrillation

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Deep Learning Based Staging of Bone Lesions From Computed Tomography Scans

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Augmenting Cervical Cancer Analysis with Deep Learning Classification and Topography Selection Using Artificial Bee Colony Optimization

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Full training convolutional neural network for ECG signals classification

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Early Feasibility of Automated Artificial Intelligence Angiography Based Fractional Flow Reserve Estimation

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COVID-19 detection from Xray and CT scans using transfer learning

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Deep Gaussian processes for multiple instance learning: Application to CT intracranial hemorrhage detection

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Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study

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Ovary Cancer Diagnosing Empowered with Machine Learning

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A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques

Ahmed, S. N., & Prakasam, P. (2023) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2023.07.001 · Cited by 36

Demonstration of the potential of white-box machine learning approaches to gain insights from cardiovascular disease electrocardiograms

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Intracranial Hemorrhage Detection Using Parallel Deep Convolutional Models and Boosting Mechanism

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An Extensive Investigation into the Use of Machine Learning Tools and Deep Neural Networks for the Recognition of Skin Cancer: Challenges, Future Directions, and a Comprehensive Review

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A Simplified Framework for the Detection of Intracranial Hemorrhage in CT Brain Images Using Deep Learning

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Tissue at Risk and Ischemic Core Estimation Using Deep Learning in Acute Stroke

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Efficiency of a deep learning-based artificial intelligence diagnostic system in spontaneous intracerebral hemorrhage volume measurement

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Emergency triage of brain computed tomography via anomaly detection with a deep generative model

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Localization of mixed intracranial hemorrhages by using a ghost convolution-based YOLO network

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A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study

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Deep learning for [18F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis

Häggström, I., Leithner, D., Alvén, J., Campanella, G. S. V., Abusamra, M., Zhang, H., Chhabra, S., Beer, L., Haug, A. R., Salles, G. A., et al. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00203-0 · Cited by 35

Applications of deep learning in trauma radiology: A narrative review

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Advancing paleontology: a survey on deep learning methodologies in fossil image analysis

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A preliminary study of deep learning-based reconstruction specialized for denoising in high-frequency domain: usefulness in high-resolution three-dimensional magnetic resonance cisternography of the cerebellopontine angle

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Deep learning for medical image analysis: a brief introduction

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Generative Adversarial Network Based Automatic Segmentation of Corneal Subbasal Nerves on In Vivo Confocal Microscopy Images

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A Computer Vision-Based Approach for Tick Identification Using Deep Learning Models

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A new argument for No-fault compensation in health care: the introduction of artificial intelligence systems

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