Published on in Vol 22, No 8 (2020): August
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/16709, first published
.
Journals
- Yu K, Hu V, Wang F, Matulonis U, Mutter G, Golden J, Kohane I. Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks. BMC Medicine 2020;18(1) View
- Chaturvedi P, Jhamb A, Vanani M, Nemade V. Prediction and Classification of Lung Cancer Using Machine Learning Techniques. IOP Conference Series: Materials Science and Engineering 2021;1099(1):012059 View
- Easwaran U, Kandasamy Y, Chellappan R, Perumal O. Impact of biomaterials in lung tumor classification and segmentation using Machine learning healthcare. Materials Today: Proceedings 2021;43:3100 View
- Althubaity D, Alotaibi F, Osman A, Al-khadher M, Abdalla Y, Alwesabi S, Abdulrahman E, Alhemairy M. Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis. Journal of Personalized Medicine 2023;13(3):388 View
- Somfai E, Baffy B, Fenech K, Hosszú R, Korózs D, Pólik M, Sárdy M, Lőrincz A. Handling dataset dependence with model ensembles for skin lesion classification from dermoscopic and clinical images. International Journal of Imaging Systems and Technology 2023;33(2):556 View
- Arzamasov K, Semenov S, Kokina D, Bobrovskaya T, Pavlov N, Kirpichev Y, Andreychenko A, Vladzymyrskyy A. Criteria for the Applicability of Computer Vision for Preventive Studies on the Example of Chest X-Ray and Fluorography. Meditsinskaya Fizika 2023;96(4):56 View
- Sohn E. The reproducibility issues that haunt health-care AI. Nature 2023;613(7943):402 View
- Banu S, Sarker M, Abdel-Nasser M, Puig D, Raswan H. AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation. Applied Sciences 2021;11(21):10132 View
- Gandomkar Z, Khong P, Punch A, Lewis S. Using Occlusion-Based Saliency Maps to Explain an Artificial Intelligence Tool in Lung Cancer Screening: Agreement Between Radiologists, Labels, and Visual Prompts. Journal of Digital Imaging 2022;35(5):1164 View
- Sonnenschein K, Stojanović S, Dickel N, Fiedler J, Bauersachs J, Thum T, Kunz M, Tongers J. Artificial Intelligence Identifies an Urgent Need for Peripheral Vascular Intervention by Multiplexing Standard Clinical Parameters. Biomedicines 2021;9(10):1456 View
- Ye M, Tong L, Zheng X, Wang H, Zhou H, Zhu X, Zhou C, Zhao P, Wang Y, Wang Q, Bai L, Cai Z, Kong F, Wang Y, Li Y, Feng M, Ye X, Yang D, Liu Z, Zhang Q, Wang Z, Han S, Sun L, Zhao N, Yu Z, Zhang J, Zhang X, Katz R, Sun J, Bai C. A Classifier for Improving Early Lung Cancer Diagnosis Incorporating Artificial Intelligence and Liquid Biopsy. Frontiers in Oncology 2022;12 View
- Cifci M. A Deep Learning-Based Framework for Uncertainty Quantification in Medical Imaging Using the DropWeak Technique: An Empirical Study with Baresnet. Diagnostics 2023;13(4):800 View
- Yan S, Huang Q, Yu S, Liu Z, Ramirez G. Computed Tomography Images under Deep Learning Algorithm in the Diagnosis of Perioperative Rehabilitation Nursing for Patients with Lung Cancer. Scientific Programming 2022;2022:1 View
- Anderson P, Gadgil R, Johnson W, Schwab E, Davidson J. Reducing variability of breast cancer subtype predictors by grounding deep learning models in prior knowledge. Computers in Biology and Medicine 2021;138:104850 View
- Tsai P, Lee T, Kuo K, Su F, Lee T, Marostica E, Ugai T, Zhao M, Lau M, Väyrynen J, Giannakis M, Takashima Y, Kahaki S, Wu K, Song M, Meyerhardt J, Chan A, Chiang J, Nowak J, Ogino S, Yu K. Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients. Nature Communications 2023;14(1) View
- Bhavani K, Gopalakrishna M. COMPARATIVE ANALYSIS OF TRADITIONAL CLASSIFICATION AND DEEP LEARNING IN LUNG CANCER PREDICTION. Biomedical Engineering: Applications, Basis and Communications 2023;35(02) View
- Arzamasov K, Vasilev Y, Vladzymyrskyy A, Omelyanskaya O, Shulkin I, Kozikhina D, Goncharova I, Gelezhe P, Kirpichev Y, Bobrovskaya T, Andreychenko A. An International Non-Inferiority Study for the Benchmarking of AI for Routine Radiology Cases: Chest X-ray, Fluorography and Mammography. Healthcare 2023;11(12):1684 View
- Moassefi M, Rouzrokh P, Conte G, Vahdati S, Fu T, Tahmasebi A, Younis M, Farahani K, Gentili A, Kline T, Kitamura F, Huo Y, Kuanar S, Younis K, Erickson B, Faghani S. Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review. Journal of Digital Imaging 2023;36(5):2306 View
- Ardimento P, Aversano L, Bernardi M, Cimitile M, Iammarino M, Verdone C. Evo-GUNet3++: Using evolutionary algorithms to train UNet-based architectures for efficient 3D lung cancer detection. Applied Soft Computing 2023;144:110465 View
- Tripathi A, Katiyar S, Mishra A. Glypican1: A potential cancer biomarker for nanotargeted therapy. Drug Discovery Today 2023;28(8):103660 View
- Reddy N, Khanaa V. Diagnosing and categorizing of pulmonary diseases using Deep learning conventional Neural network. International Journal of Experimental Research and Review 2023;31(Spl Volume):12 View
- Rani K, Sumathy G, Shoba L, Shermila P, Prince M. Radon transform-based improved single seeded region growing segmentation for lung cancer detection using AMPWSVM classification approach. Signal, Image and Video Processing 2023;17(8):4571 View
- Yue Y, Kong F, Cheng M, Cao H, Qi J, Shi Z. KFS-Net: Key Features Sampling Network for Lung Nodule Segmentation. Sensing and Imaging 2023;25(1) View
- Parveen R, Saleem U, Abid K, Aslam N. Identification of Lungs Cancer by using Watershed Machine Learning Algorithm. VFAST Transactions on Software Engineering 2023;11(2):70 View
- Gayap H, Akhloufi M. Deep Machine Learning for Medical Diagnosis, Application to Lung Cancer Detection: A Review. BioMedInformatics 2024;4(1):236 View
- Saeki Y, Maki N, Nemoto T, Inada K, Minami K, Tamura R, Imamura G, Cho-Isoda Y, Kitazawa S, Kojima H, Yoshikawa G, Sato Y. Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array. Lung Cancer 2024;190:107514 View
- Lasko T, Strobl E, Stead W. Why do probabilistic clinical models fail to transport between sites. npj Digital Medicine 2024;7(1) View
- Zhang Y, Xiao L, LYu L, Zhang L. Construction of a predictive model for bone metastasis from first primary lung adenocarcinoma within 3 cm based on machine learning algorithm: a retrospective study. PeerJ 2024;12:e17098 View
- Tai D, Nhu N, Tuan P, Sulieman A, Omer H, Alirezaei Z, Bradley D, Chow J. A user-friendly deep learning application for accurate lung cancer diagnosis. Journal of X-Ray Science and Technology 2024;32(3):611 View
- Drazen J, Yu K, Healey E, Leong T, Kohane I, Manrai A. Medical Artificial Intelligence and Human Values. New England Journal of Medicine 2024;390(20):1895 View
- Marinakis I, Karampidis K, Papadourakis G. Pulmonary Nodule Detection, Segmentation and Classification Using Deep Learning: A Comprehensive Literature Review. BioMedInformatics 2024;4(3):2043 View
- Hashmi A, Ali W, Abulfaraj A, Binzagr F, Alkayal E. Enhancing Cancerous Gene Selection and Classification for High-Dimensional Microarray Data Using a Novel Hybrid Filter and Differential Evolutionary Feature Selection. Cancers 2024;16(23):3913 View
Books/Policy Documents
- Barrachina M, Valenzuela L. Artificial Intelligence for Societal Development and Global Well-Being. View
- Kashyap S, Shukla A, Naim I. AI and IoT-Based Technologies for Precision Medicine. View
- Sudhir Reddy N, Khanaa V. Intelligent Systems and Sustainable Computing. View
- Sundarrajan M, Perumal S, Sasikala S, Ramachandran M, Pradeep N. Advances in Explainable AI Applications for Smart Cities. View
- Sohaib M. Universal Access in Human-Computer Interaction. View