From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment

K Swanson, E Wu, A Zhang, AA Alizadeh, J Zou - Cell, 2023 - cell.com
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

[HTML][HTML] Artificial intelligence and computational pathology

M Cui, DY Zhang - Laboratory Investigation, 2021 - Elsevier
Data processing and learning has become a spearhead for the advancement of medicine,
with pathology and laboratory medicine has no exception. The incorporation of scientific …

Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges

S Huang, J Yang, S Fong, Q Zhao - Cancer letters, 2020 - Elsevier
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 …

Multi-disease prediction based on deep learning: a survey

S Xie, Z Yu, Z Lv - Computer Modeling in Engineering & …, 2021 - ingentaconnect.com
In recent years, the development of artificial intelligence (AI) and the gradual beginning of
AI's research in the medical field have allowed people to see the excellent prospects of the …

The application of deep learning in cancer prognosis prediction

W Zhu, L Xie, J Han, X Guo - Cancers, 2020 - mdpi.com
Deep learning has been applied to many areas in health care, including imaging diagnosis,
digital pathology, prediction of hospital admission, drug design, classification of cancer and …

Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward.

E Elyan, P Vuttipittayamongkol… - Artificial …, 2022 - rgu-repository.worktribe.com
The recent development in the areas of deep learning and deep convolutional neural
networks has significantly progressed and advanced the field of computer vision (CV) and …

Artificial intelligence surgery: How do we get to autonomous actions in surgery?

AA Gumbs, I Frigerio, G Spolverato, R Croner, A Illanes… - Sensors, 2021 - mdpi.com
Most surgeons are skeptical as to the feasibility of autonomous actions in surgery.
Interestingly, many examples of autonomous actions already exist and have been around for …

Adversarial machine learning in wireless communications using RF data: A review

D Adesina, CC Hsieh, YE Sagduyu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …

[HTML][HTML] An overview of deep learning in medical imaging

A Anaya-Isaza, L Mera-Jiménez… - Informatics in medicine …, 2021 - Elsevier
Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …

Biology and medicine in the landscape of quantum advantages

BA Cordier, NPD Sawaya… - Journal of the …, 2022 - royalsocietypublishing.org
Quantum computing holds substantial potential for applications in biology and medicine,
spanning from the simulation of biomolecules to machine learning methods for subtyping …