Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

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Contour Detection and Hierarchical Image Segmentation

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Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

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The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

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Distance Regularized Level Set Evolution and Its Application to Image Segmentation

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Exploring Strategies for Training Deep Neural Networks

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Bringing Machine Learning Systems into Clinical Practice: A Design Science Approach to Explainable Machine Learning-Based Clinical Decision Support Systems

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Is Intensity Inhomogeneity Correction Useful for Classification of Breast Cancer in Sonograms Using Deep Neural Network?

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The Use of Deep Convolutional Neural Networks in Biomedical Imaging: A Review

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Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT

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A deep learning model for the differential diagnosis of benign and malignant salivary gland tumors based on ultrasound imaging and clinical data

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Applying 3D U-Net Architecture to the Task of Multi-Organ Segmentation in Computed Tomography

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A Review of the Clinical Applications of Artificial Intelligence in Abdominal Imaging

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Visual Analytics of a Computer-Aided Diagnosis System for Pancreatic Lesions

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MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning

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Artificial intelligence in the GPs office: a retrospective study on diagnostic accuracy

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Benign-malignant classification of pulmonary nodule with deep feature optimization framework

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Improvement of Heterogeneous Transfer Learning Efficiency by Using Hebbian Learning Principle

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Pose recognition using convolutional neural networks on omni-directional images

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Pre-Training Autoencoder for Lung Nodule Malignancy Assessment Using CT Images

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

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A computing system that integrates deep learning and the internet of things for effective disease diagnosis in smart health care systems

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Identification of Barrett's esophagus in endoscopic images using deep learning

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DeAF: A multimodal deep learning framework for disease prediction

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Deep Learning for Medical Image Analysis: Applications to Computed Tomography and Magnetic Resonance Imaging

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A novel deep mining model for effective knowledge discovery from omics data

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Deep Learning-assisted Diagnosis of Breast Lesions on US Images: A Multivendor, Multicenter Study

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Artificial intelligence for predicting treatment responses in autoimmune rheumatic diseases: advancements, challenges, and future perspectives

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The Promise of Clinical Decision Support Systems Targetting Low-Resource Settings

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Predicting the Prognosis of MCI Patients Using Longitudinal MRI Data

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A 3D Deep Residual Convolutional Neural Network for Differential Diagnosis of Parkinsonian Syndromes on 18F-FDG PET Images

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A Tour of Unsupervised Deep Learning for Medical Image Analysis

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Medical Text and Image Processing: Applications, Issues and Challenges

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Detection and recognition of ultrasound breast nodules based on semi-supervised deep learning: a powerful alternative strategy

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New Optimized Deep Learning Application for COVID-19 Detection in Chest X-ray Images

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Analysis of the Causes of Solitary Pulmonary Nodule Misdiagnosed as Lung Cancer by Using Artificial Intelligence: A Retrospective Study at a Single Center

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Imagerie médicale computationnelle (radiomique) et potentiel en immuno-oncologie

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Applying Machine Learning for Integration of Multi-Modal Genomics Data and Imaging Data to Quantify Heterogeneity in Tumour Tissues

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On the robustness of deep learning-based lung-nodule classification for CT images with respect to image noise

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A Justifiable Investment in AI for Healthcare: Aligning Ambition with Reality

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Deep Learning in Radiology: Now the Real Work Begins

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Diagnosis of hypercritical chronic pulmonary disorders using dense convolutional network through chest radiography

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The role of artificial intelligence in paediatric neuroradiology

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Deep learning with transfer learning in pathology. Case study: classification of basal cell carcinoma

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The use of deep learning to automate the segmentation of the skeleton from CT volumes of pigs1

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An investigation of the classification accuracy of a deep learning framework-based computer-aided diagnosis system in different pathological types of breast lesions

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Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening

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Detection of Lung Cancer on Computed Tomography Using Artificial Intelligence Applications Developed by Deep Learning Methods and the Contribution of Deep Learning to the Classification of Lung Carcinoma

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Automated Detection of Epiretinal Membranes in OCT Images Using Deep Learning

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Application of Neural Networks in the Medical Field

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Toward next-generation endoscopes integrating biomimetic video systems, nonlinear optical microscopy, and deep learning

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Application of Compressive Sensing to Ultrasound Images: A Review

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Automatic detection of adenoid hypertrophy on cone-beam computed tomography based on deep learning

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Diagnostic Performance of Ultrasound Computer-Aided Diagnosis Software Compared with That of Radiologists with Different Levels of Expertise for Thyroid Malignancy: A Multicenter Prospective Study

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DeepHealth: Review and challenges of artificial intelligence in health informaticsPreprint

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Detecting and classifying hidden defects in additively manufactured parts using deep learning and X-ray computed tomography

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Can Contrast-Enhanced Ultrasound Increase or Predict the Success Rate of Testicular Sperm Aspiration in Patients With Azoospermia?

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Competitive Deep Learning Methods for COVID-19 Detection using X-ray Images

Swapnarekha, H., Behera, H. S., Roy, D., Das, S., & Nayak, J. (2021) · Journal of The Institution of Engineers (India) Series B · doi:10.1007/s40031-021-00589-3 · Cited by 19

A deep learning method to detect opioid prescription and opioid use disorder from electronic health records

Kashyap, A., Callison-Burch, C., & Boland, M. R. (2022) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2022.104979 · Cited by 21

MsGoF: Breast lesion classification on ultrasound images by multi-scale gradational-order fusion framework

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A Novel Hybrid Feature Extraction Model for Classification on Pulmonary Nodules

Kailasam, S. P., & Sathik, M. M. (2019) · Asian Pacific Journal of Cancer Prevention · doi:10.31557/apjcp.2019.20.2.457 · Cited by 19

Artificial Intelligence in Ultrasound Imaging: Current Research and Applications

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A bimodal BI-RADS-guided GoogLeNet-based CAD system for solid breast masses discrimination using transfer learning

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Saliency map-guided hierarchical dense feature aggregation framework for breast lesion classification using ultrasound image

Di, X., Zhong, S., & Zhang, Y. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106612 · Cited by 20

Application of CT and MRI images based on artificial intelligence to predict lymph node metastases in patients with oral squamous cell carcinoma: a subgroup meta-analysis

Deng, C., Hu, J., Tang, P., Xu, T., He, L. F., Zeng, Z., & Sheng, J. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1395159 · Cited by 18

Deep Learning Application for Analyzing of Constituents and Their Correlations in the Interpretations of Medical Images

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Assessment of an Artificial Intelligence Mandibular Osteotomy Design System: A Retrospective Study

Qiu, X., Han, W., Dai, L., Zhang, Y., Zhang, J., Chai, G., Lin, L., & Zhou, J. (2022) · Aesthetic Plastic Surgery · doi:10.1007/s00266-021-02698-2 · Cited by 17

Robust multi-modal prostate cancer classification via feature autoencoder and dual attention

Li, B., Oka, R., Xuan, P., Yoshimura, Y., & Nakaguchi, T. (2022) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2022.100923 · Cited by 18

Adaption of the Aristotle Classifier for Accurately Identifying Highly Similar Bacteria Analyzed by MALDI-TOF MS

Desaire, H., & Hua, D. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b04049 · Cited by 18

Improving disease prevention, diagnosis, and treatment using novel bionic technologies

Manero, A. C., Crawford, K. E., Gibbs, H. P., Shah, N., Gandhi, D. A., & Coathup, M. J. (2022) · Bioengineering & Translational Medicine · doi:10.1002/btm2.10359 · Cited by 18

A validation of an entropy-based artificial intelligence for ultrasound data in breast tumors

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Proposing a deep learning-based method for improving the diagnostic certainty of pulmonary nodules in CT scan of chest

Wang, Y., Wang, J., Yang, S.-X., Qi, L., Lin, H., Zhou, Z., & Yu, Y. (2021) · European Radiology · doi:10.1007/s00330-021-07919-5 · Cited by 17

Deep learning of renal scans in children with antenatal hydronephrosis

Weaver, J. K., Logan, J. R., Broms, R., Antony, M., Rickard, M., Erdman, L., Edwins, R. C., Pominville, R., Hannick, J. H., Woo, L. L., et al. (2023) · Journal of Pediatric Urology · doi:10.1016/j.jpurol.2022.12.017 · Cited by 17

SinusC-Net for automatic classification of surgical plans for maxillary sinus augmentation using a 3D distance-guided network

Hwang, I.-K., Kang, S.-R., Yang, S., Kim, J.-M., Kim, J., Huh, K., Lee, S.-S., Heo, M.-S., Yi, W.-J., & Kim, T. (2023) · Scientific Reports · doi:10.1038/s41598-023-38273-9 · Cited by 17

Artificial Intelligence for Contrast-Enhanced Ultrasound of the Liver: A Systematic Review

Brooks, J. A., Kallenbach, M., Radu, I.-P., Berzigotti, A., Dietrich, C. F., Kather, J. N., Luedde, T., & Seraphin, T. P. (2024) · Digestion · doi:10.1159/000541540 · Cited by 17

Multi-scale Gradational-Order Fusion Framework for Breast Lesions Classification Using Ultrasound Images

Ning, Z., Tu, C., Xiao, Q., Luo, J., & Zhang, Y. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59725-2_17 · Cited by 17

Medical Image Classification Algorithm Based on Weight Initialization‐Sliding Window Fusion Convolutional Neural Network

An, F.-P. (2019) · Complexity · doi:10.1155/2019/9151670 · Cited by 17

Combination of deep learning and ensemble machine learning using intraoperative video images strongly predicts recovery of urinary continence after robot‐assisted radical prostatectomy

Nakamura, W., Sumitomo, M., Zennami, K., Takenaka, M., Ichino, M., Takahara, K., Teramoto, A., & Shiroki, R. (2023) · Cancer Reports · doi:10.1002/cnr2.1861 · Cited by 17

Defense against adversarial attacks based on color space transformation

Wang, H., Wu, C., & Zheng, K. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106176 · Cited by 17

Review of AI & XAI-based breast cancer diagnosis methods using various imaging modalities

Karthiga, R., Narasimhan, K., Thanikaiselvan, V., Hemalatha, M., & Amirtharajan, R. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20271-2 · Cited by 20

A dual-mode deep transfer learning (D2TL) system for breast cancer detection using contrast enhanced digital mammograms

Wang, K., Patel, B., Wang, L., Wu, T., Zheng, B., & Li, J. (2019) · IISE Transactions on Healthcare Systems Engineering · doi:10.1080/24725579.2019.1628133 · Cited by 16

Regulatory issues for artificial intelligence in radiology

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Computer-aided diagnosis of pectus excavatum using CT images and deep learning methods

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A Review of Machine Learning Methodologies for Dental Disease Detection

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Deep Convolutional Neural Network for Computer-Aided Detection of Breast Cancer Using Histopathology Images

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Deep Learning in IoT

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Esophageal cancer detection via non-contrast CT and deep learning

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Deep learning-based spinal canal segmentation of computed tomography image for disease diagnosis: A proposed system for spinal stenosis diagnosis

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CAESNet: Convolutional AutoEncoder based Semi-supervised Network for improving multiclass classification of endomicroscopic images

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A Characterization Approach for the Review of CAD Systems Designed for Breast Tumor Classification Using B-Mode Ultrasound Images

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Bioinformatics and Medicine in the Era of Deep Learning

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The semantic segmentation approach for normal and pathologic tympanic membrane using deep learningPreprint

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Artificial Intelligence—What to Expect From Machine Learning and Deep Learning in Hernia Surgery

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