Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges
Cancer is an aggressive disease with a low median survival rate. Ironically, the treatment
process is long and very costly due to its high recurrence and mortality rates. Accurate early …
process is long and very costly due to its high recurrence and mortality rates. Accurate early …
[HTML][HTML] Machine learning applications in cancer prognosis and prediction
Cancer has been characterized as a heterogeneous disease consisting of many different
subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in …
subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in …
[HTML][HTML] MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification
To fully utilize the advances in omics technologies and achieve a more comprehensive
understanding of human diseases, novel computational methods are required for integrative …
understanding of human diseases, novel computational methods are required for integrative …
A multimodal deep neural network for human breast cancer prognosis prediction by integrating multi-dimensional data
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 …
prognosis prediction of breast cancer can spare a significant number of patients from …
[PDF][PDF] Descriptive analysis of machine learning and its application in healthcare
SS Gadde, VDR Kalli - Int J Comp Sci Trends Technol, 2020 - academia.edu
The dynamic world of big data in the healthcare sector characterized by huge numbers,
complexity, and speeds is also not suited to conventional research methods. Methods are …
complexity, and speeds is also not suited to conventional research methods. Methods are …
[HTML][HTML] Artificial intelligence in pharmaceutical sciences
Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …
impacts the pharmaceutical market. However, investments in a new drug often go …
Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach
CC Bennett, K Hauser - Artificial intelligence in medicine, 2013 - Elsevier
OBJECTIVE: In the modern healthcare system, rapidly expanding costs/complexity, the
growing myriad of treatment options, and exploding information streams that often do not …
growing myriad of treatment options, and exploding information streams that often do not …
Multi-modal advanced deep learning architectures for breast cancer survival prediction
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 …
increasing mortality rates among women. The manual prognosis and diagnosis of this …
[HTML][HTML] Breast cancer prognosis using a machine learning approach
Machine learning (ML) has been recently introduced to develop prognostic classification
models that can be used to predict outcomes in individual cancer patients. Here, we report …
models that can be used to predict outcomes in individual cancer patients. Here, we report …
Small-sample precision of ROC-related estimates
Motivation: The receiver operator characteristic (ROC) curves are commonly used in
biomedical applications to judge the performance of a discriminant across varying decision …
biomedical applications to judge the performance of a discriminant across varying decision …