Artificial intelligence in gynecologic cancers: Current status and future challenges–A systematic review

M Akazawa, K Hashimoto - Artificial Intelligence in Medicine, 2021 - Elsevier
Objective Over the past years, the application of artificial intelligence (AI) in medicine has
increased rapidly, especially in diagnostics, and in the near future, the role of AI in medicine …

[HTML][HTML] An overview of deep learning in medical imaging

A Anaya-Isaza, L Mera-Jiménez… - Informatics in medicine …, 2021 - Elsevier
Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …

[HTML][HTML] Factors predicting surgical effort using explainable artificial intelligence in advanced stage epithelial ovarian cancer

A Laios, E Kalampokis, R Johnson, S Munot… - Cancers, 2022 - mdpi.com
Simple Summary In the era of personalized medicine, Artificial Intelligence (AI) has emerged
as a powerful tool with growing applications in the field of gynaecologic oncology. However …

[HTML][HTML] A systematic review on the use of artificial intelligence in gynecologic imaging–background, state of the art, and future directions

P Shrestha, B Poudyal, S Yadollahi, DE Wright… - Gynecologic …, 2022 - Elsevier
Objective Machine learning, deep learning, and artificial intelligence (AI) are terms that have
made their way into nearly all areas of medicine. In the case of medical imaging, these …

Application of artificial intelligence in gynecologic malignancies: A review

K Sone, Y Toyohara, A Taguchi… - Journal of Obstetrics …, 2021 - Wiley Online Library
With the development of machine learning and deep learning models, artificial intelligence
is now being applied to the field of medicine. In oncology, the use of artificial intelligence for …

[HTML][HTML] Diagnosing ovarian cancer on MRI: a preliminary study comparing deep learning and radiologist assessments

T Saida, K Mori, S Hoshiai, M Sakai, A Urushibara… - Cancers, 2022 - mdpi.com
Simple Summary As a preliminary experiment to explore the possibility of clinical application
as a future reading assist, we present CNNs for the diagnosis of ovarian carcinomas and …

[HTML][HTML] Recent imaging updates and advances in gynecologic malignancies

T Daoud, S Sardana, N Stanietzky, AR Klekers… - Cancers, 2022 - mdpi.com
Simple Summary Gynecological malignancies are among the most common cancers with
significant morbidity and mortality worldwide. Management and overall patient survival is …

[HTML][HTML] The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists

A Urushibara, T Saida, K Mori, T Ishiguro, K Inoue… - BMC Medical …, 2022 - Springer
Purpose To compare the diagnostic performance of deep learning models using
convolutional neural networks (CNN) with that of radiologists in diagnosing endometrial …

Artificial intelligence (AI) in the detection of rectosigmoid deep endometriosis

S Guerriero, MA Pascual, S Ajossa, M Neri… - European Journal of …, 2021 - Elsevier
Objectives The aim of this study was to compare the accuracy of seven classical Machine
Learning (ML) models trained with ultrasound (US) soft markers to raise suspicion of …

Clinical artificial intelligence applications in radiology: chest and abdomen

S Lee, RM Summers - Radiologic Clinics, 2021 - radiologic.theclinics.com
How wonderful would it be if an automated assistant would go through our daily chest
radiographs and sort out the ones that need our immediate attention; or maybe pick out the …