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Showing 8 of 8 academic articles

Nanostructured transdermal hormone replacement therapy for relieving menopausal symptoms: a confocal Raman spectroscopy study

Marco Antonio Botelho, Dinalva Brito Queiroz, Gisele Barros, Stela Guerreiro et al. • Clinics (2014)

OBJECTIVE: To determine the safety and efficacy of a transdermal nanostructured formulation of progesterone (10%) combined with estriol (0.1%) + estradiol (0.25%) for relieving postmenopausal symptoms. METHODS: A total of 66 postmenopausa...

DOAJ Open Access (DOAJ) DOI: 10.6061/clinics/2014(02)01

Computer‐aided diagnosis in the era of deep learning

Heang‐Ping Chan, Lubomir M. Hadjiiski, Ravi K. Samala • Medical Physics (2020)

Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then ...

OPENALEX Open Access DOI: https://doi.org/10.1002/mp.13764 PMC: 7293164

Deep Learning in Mammography

Anton S. Becker, Magda Marcon, Soleen Ghafoor, Moritz C. Wurnig et al. • Investigative Radiology (2017)

OBJECTIVES: The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an independent, dual-center mam...

OPENALEX DOI: https://doi.org/10.1097/rli.0000000000000358

A cascaded classification approach using transfer learning and feature engineering for improved breast cancer classification

Chokri Ferkous, Ouissal Fadel, Abderrahmane Kefali, Hayet-Farida Merouani • IJAIN (International Journal of Advances in Intelligent Informatics) (2026)

The primary objective of this study is to design a cascaded classification framework that integrates deep-learning representations with handcrafted and clinical features to enhance the reliability and accuracy of breast cancer detection in ...

DOAJ Open Access (DOAJ) DOI: 10.26555/ijain.v12i1.1670

Women’s perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study

Jennifer Viberg Johansson, Karin Dembrower, Fredrik Strand, Åsa Grauman • BMJ Open (2024)

Background Understanding women’s perspectives can help to create an effective and acceptable artificial intelligence (AI) implementation for triaging mammograms, ensuring a high proportion of screening-detected cancer. This study aimed to e...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjopen-2024-084014