Deep learning for health informatics

D Ravì, C Wong, F Deligianni… - IEEE journal of …, 2016 - ieeexplore.ieee.org
With a massive influx of multimodality data, the role of data analytics in health informatics
has grown rapidly in the last decade. This has also prompted increasing interests in the …

A comprehensive survey on deep-learning-based breast cancer diagnosis

MF Mridha, MA Hamid, MM Monowar, AJ Keya, AQ Ohi… - Cancers, 2021 - mdpi.com
Simple Summary Breast cancer was diagnosed in 2.3 million women, and around 685,000
deaths from breast cancer were recorded globally in 2020, making it the most common …

[PDF][PDF] Adaptive dynamic dipper throated optimization for feature selection in medical data

G Atteia, ESM El-kenawy, NA Samee… - … , Materials & Continua, 2023 - academia.edu
The rapid population growth results in a crucial problem in the early detection of diseases in
medical research. Among all the cancers unveiled, breast cancer is considered the second …

A multimodal deep neural network for human breast cancer prognosis prediction by integrating multi-dimensional data

D Sun, M Wang, A Li - IEEE/ACM transactions on …, 2018 - ieeexplore.ieee.org
Breast cancer is a highly aggressive type of cancer with very low median survival. Accurate
prognosis prediction of breast cancer can spare a significant number of patients from …

[HTML][HTML] Bayesian networks in healthcare: Distribution by medical condition

S McLachlan, K Dube, GA Hitman, NE Fenton… - Artificial intelligence in …, 2020 - Elsevier
Bayesian networks (BNs) have received increasing research attention that is not matched by
adoption in practice and yet have potential to significantly benefit healthcare. Hitherto …

Multi-modal advanced deep learning architectures for breast cancer survival prediction

N Arya, S Saha - Knowledge-Based Systems, 2021 - Elsevier
Breast cancer is the most frequently occurring cancer and has compelling contributions to
increasing mortality rates among women. The manual prognosis and diagnosis of this …

Deep learning in omics: a survey and guideline

Z Zhang, Y Zhao, X Liao, W Shi, K Li… - Briefings in functional …, 2019 - academic.oup.com
Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big
data. A huge amount of high dimensional and complex structured data has made it no …

A comprehensive sco** review of Bayesian networks in healthcare: Past, present and future

E Kyrimi, S McLachlan, K Dube, MR Neves… - Artificial Intelligence in …, 2021 - Elsevier
No comprehensive review of Bayesian networks (BNs) in healthcare has been published in
the past, making it difficult to organize the research contributions in the present and identify …

Multi-modal classification for human breast cancer prognosis prediction: proposal of deep-learning based stacked ensemble model

N Arya, S Saha - IEEE/ACM transactions on computational …, 2020 - ieeexplore.ieee.org
Breast Cancer is a highly aggressive type of cancer generally formed in the cells of the
breast. Despite significant advances in the treatment of primary breast cancer in the last …

Integrating genomic data and pathological images to effectively predict breast cancer clinical outcome

D Sun, A Li, B Tang, M Wang - Computer methods and programs in …, 2018 - Elsevier
Background and objective Breast cancer is a leading cause of death from cancer for
females. The high mortality rate of breast cancer is largely due to the complexity among …