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Showing 8 of 48 academic articles

Deep Learning in Medical Image Analysis

Dinggang G. Shen, Guorong Wu A, Heung‐Il Suk • Annual Review of Biomedical Engineering (2017)

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical image...

OPENALEX Open Access DOI: https://doi.org/10.1146/annurev-bioeng-071516-044442 PMC: 5479722

PCPAm - A dataset of histopathological images of penile cancer for classification tasksZenodo

Marcos Gabriel Mendes Lauande, Geraldo Braz Júnior, João Dallyson Sousa de Almeida, Vandecia Rejane Monteiro Fernandes et al. • Data in Brief (2025)

Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underdeveloped countries like Brazil, where it represents approximately 2% of cancers affecting men. This dataset was created to address the scarc...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2025.111823

Machine Learning for Medical Imaging

Bradley James Erickson, Panagiotis D. Korfiatis, Zeynettin Akkus, Timothy Lee Kline • Radiographics (2017)

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the ma...

OPENALEX Open Access DOI: https://doi.org/10.1148/rg.2017160130 PMC: 5375621

Artificial intelligence in pancreatic cancer

Bowen Huang, Haoran Huang, Shuting Zhang, Dingyue Zhang et al. • Theranostics (2022)

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early screening have a median overall survival of nearly ten years, compared with 1.5 years for th...

OPENALEX cc-by DOI: https://doi.org/10.7150/thno.77949 PMC: 9576619

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Song Zeng, Xin-Lu Wang, Hua Yang • Military Medical Research (2024)

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40779-024-00580-1

Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

Yu Jiang Master of Engineering, Kang Wang Master of Medicine, Yu-Ran Wang Master of Engineering, Yan-Jun Xiang Master of Medicine et al. • Technology in Cancer Research & Treatment (2023)

Microvascular invasion of hepatocellular carcinoma is an important factor affecting tumor recurrence after liver resection and liver transplantation. There are many ways to classify microvascular invasion, however, an international consensu...

DOAJ Open Access (DOAJ) DOI: 10.1177/15330338231212726