Deep learning in cancer diagnosis and prognosis prediction: a minireview on challenges, recent trends, and future directions

AB Tufail, YK Ma, MKA Kaabar… - … Methods in Medicine, 2021 - Wiley Online Library
Deep learning (DL) is a branch of machine learning and artificial intelligence that has been
applied to many areas in different domains such as health care and drug design. Cancer …

Artificial intelligence applications in medical imaging: A review of the medical physics research in Italy

M Avanzo, M Porzio, L Lorenzon, L Milan, R Sghedoni… - Physica Medica, 2021 - Elsevier
Purpose To perform a systematic review on the research on the application of artificial
intelligence (AI) to imaging published in Italy and identify its fields of application, methods …

[HTML][HTML] An investigation of XGBoost-based algorithm for breast cancer classification

XY Liew, N Hameed, J Clos - Machine Learning with Applications, 2021 - Elsevier
Breast cancer is one of the leading cancers affecting women around the world. The
Computer-Aided Diagnosis (CAD) system is a powerful tool to assist pathologists during the …

Survey on machine learning and deep learning applications in breast cancer diagnosis

G Chugh, S Kumar, N Singh - Cognitive Computation, 2021 - Springer
Cancer is a fatal disease caused due to the undesirable spread of cells. Breast carcinoma is
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …

Encoder enhanced atrous (EEA) unet architecture for retinal blood vessel segmentation

V Sathananthavathi, G Indumathi - Cognitive Systems Research, 2021 - Elsevier
The retinal blood vessel segmentation is required for continuously monitoring the blood
vessel in most of the retinal disease diagnosis. Deep learning approaches are accepted as …

[HTML][HTML] Spatiotemporally explicit earthquake prediction using deep neural network

M Yousefzadeh, SA Hosseini, M Farnaghi - Soil Dynamics and Earthquake …, 2021 - Elsevier
Due to the complexity of predicting future earthquakes, machine learning algorithms have
been used by several researchers to increase the Accuracy of the forecast. However, the …

A systematic literature review of breast cancer diagnosis using machine intelligence techniques

V Nemade, S Pathak, AK Dubey - Archives of Computational Methods in …, 2022 - Springer
Breast cancer is one of the most common diseases in women; it can have long-term
implications and can even be fatal. However, early detection, achieved through recent …

A compact convolutional neural network augmented with multiscale feature extraction of acquired monitoring data for mechanical intelligent fault diagnosis

K Zhang, J Chen, T Zhang, Z Zhou - Journal of Manufacturing Systems, 2020 - Elsevier
Considering all the monitoring data of bearings until failure, very few data are acquired
when the bearings are faulty. Such circumstance leads to small faulty sample problem when …

Intelligent fault diagnosis of mechanical equipment under varying working condition via iterative matching network augmented with selective Signal reuse strategy

K Zhang, J Chen, T Zhang, S He, T Pan… - Journal of Manufacturing …, 2020 - Elsevier
Change of working condition leads to discrepancy in domain distribution of equipment
vibration signals. This discrepancy poses an obstacle to application of deep learning …

[HTML][HTML] AI applications in robotics, diagnostic image analysis and precision medicine: Current limitations, future trends, guidelines on CAD systems for medicine

T Habuza, AN Navaz, F Hashim, F Alnajjar… - Informatics in Medicine …, 2021 - Elsevier
Background AI in healthcare has been recognized by both academia and industry in
revolutionizing how healthcare services will be offered by healthcare service providers and …