Applying deep learning for breast cancer detection in radiology

E Mahoro, MA Akhloufi - Current Oncology, 2022 - mdpi.com
Recent advances in deep learning have enhanced medical imaging research. Breast cancer
is the most prevalent cancer among women, and many applications have been developed to …

[HTML][HTML] Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine

VB Mathema, P Sen, S Lamichhane, M Orešič… - Computational and …, 2023 - Elsevier
Cancer progression is linked to gene-environment interactions that alter cellular
homeostasis. The use of biomarkers as early indicators of disease manifestation and …

ResNet-32 and FastAI for diagnoses of ductal carcinoma from 2D tissue slides

SP Praveen, PN Srinivasu, J Shafi, M Wozniak… - Scientific Reports, 2022 - nature.com
Carcinoma is a primary source of morbidity in women globally, with metastatic disease
accounting for most deaths. Its early discovery and diagnosis may significantly increase the …

BreaST-Net: Multi-class classification of breast cancer from histopathological images using ensemble of swin transformers

S Tummala, J Kim, S Kadry - Mathematics, 2022 - mdpi.com
Breast cancer (BC) is one of the deadly forms of cancer, causing mortality worldwide in the
female population. The standard imaging procedures for screening BC involve …

Deep Learning for Automated Lesion Detection in Mammography

T Marimuthu, VA Rajan, GV Londhe… - 2023 IEEE 2nd …, 2023 - ieeexplore.ieee.org
Deep learning for automated lesion detection in mammography has gained widespread
attention due to its potential to reduce the time needed for radiologists to detect lesions …

Forest fire surveillance systems: A review of deep learning methods

A Saleh, MA Zulkifley, HH Harun, F Gaudreault… - Heliyon, 2024 - cell.com
This review aims to critically examine the existing state-of-the-art forest fire detection
systems that are based on deep learning methods. In general, forest fire incidences bring …

Enhancing ductal carcinoma classification using transfer learning with 3D U-net models in breast cancer imaging

S Khalil, U Nawaz, Zubariah, Z Mushtaq, S Arif… - Applied Sciences, 2023 - mdpi.com
Breast cancer ranks among the leading causes of death for women globally, making it
imperative to swiftly and precisely detect the condition to ensure timely treatment and …

[HTML][HTML] A novel fusion framework of deep bottleneck residual convolutional neural network for breast cancer classification from mammogram images

K Jabeen, MA Khan, MA Hameed, O Alqahtani… - Frontiers in …, 2024 - frontiersin.org
With over 2.1 million new cases of breast cancer diagnosed annually, the incidence and
mortality rate of this disease pose severe global health issues for women. Identifying the …

Deep-learning enabled ultrasound based detection of gallbladder cancer in northern India: a prospective diagnostic study

P Gupta, S Basu, P Rana, U Dutta… - The Lancet Regional …, 2024 - thelancet.com
Background Gallbladder cancer (GBC) is highly aggressive. Diagnosis of GBC is
challenging as benign gallbladder lesions can have similar imaging features. We aim to …

Future of artificial intelligence applications in cancer care: a global cross-sectional survey of researchers

BP Cabral, LAM Braga, S Syed-Abdul, FB Mota - Current Oncology, 2023 - mdpi.com
Cancer significantly contributes to global mortality, with 9.3 million annual deaths. To
alleviate this burden, the utilization of artificial intelligence (AI) applications has been …