Artificial intelligence applications in prostate cancer

A Baydoun, AY Jia, NG Zaorsky, R Kashani… - Prostate cancer and …, 2024 - nature.com
Artificial intelligence (AI) applications have enabled remarkable advancements in healthcare
delivery. These AI tools are often aimed to improve accuracy and efficiency of histopathology …

Artificial intelligence, machine learning, and deep learning for clinical outcome prediction

RW Pettit, R Fullem, C Cheng… - Emerging topics in life …, 2021 - portlandpress.com
AI is a broad concept, grouping initiatives that use a computer to perform tasks that would
usually require a human to complete. AI methods are well suited to predict clinical outcomes …

Medical image augmentation for lesion detection using a texture-constrained multichannel progressive GAN

Q Guan, Y Chen, Z Wei, AA Heidari, H Hu… - Computers in Biology …, 2022 - Elsevier
Lesion detectors based on deep learning can assist doctors in diagnosing diseases.
However, the performance of current detectors is likely to be unsatisfactory due to the …

Deep learning for radiotherapy outcome prediction using dose data–a review

AL Appelt, B Elhaminia, A Gooya, A Gilbert, M Nix - Clinical Oncology, 2022 - Elsevier
Artificial intelligence, and in particular deep learning using convolutional neural networks,
has been used extensively for image classification and segmentation, including on medical …

[HTML][HTML] Infrastructure platform for privacy-preserving distributed machine learning development of computer-assisted theragnostics in cancer

M Field, DI Thwaites, M Carolan, GP Delaney… - Journal of Biomedical …, 2022 - Elsevier
Introduction Emerging evidence suggests that data-driven support tools have found their
way into clinical decision-making in a number of areas, including cancer care. Improving …

[PDF][PDF] Machine learning theory in building energy modeling and optimization: a bibliometric analysis

A Ghoshchi, R Zahedi, ZM Pour, A Ahmadi - J Mod Green Energy, 2022 - researchgate.net
In recent decades, the machine learning theory has been developed in the field of artificial
intelligence (AI), as it excludes all shortcomings of manpower, performs complex …

Comparison of atlas-based and deep learning methods for organs at risk delineation on head-and-neck CT images using an automated treatment planning system

M Costea, A Zlate, M Durand, T Baudier… - Radiotherapy and …, 2022 - Elsevier
Background and purpose To investigate the performance of head-and-neck (HN) organs-at-
risk (OAR) automatic segmentation (AS) using four atlas-based (ABAS) and two deep …

deepPERFECT: novel deep learning CT synthesis method for expeditious pancreatic cancer radiotherapy

H Hooshangnejad, Q Chen, X Feng, R Zhang, K Ding - Cancers, 2023 - mdpi.com
Simple Summary Pancreatic cancer is a devastating disease with more than 60,000 new
cases each year and a less than 10 percent 3-year overall survival rate. Radiation therapy is …

Current status and future developments in predicting outcomes in radiation oncology

D Niraula, S Cui, J Pakela, L Wei, Y Luo… - The British Journal of …, 2022 - academic.oup.com
Advancements in data-driven technologies and the inclusion of information-rich multiomics
features have significantly improved the performance of outcomes modeling in radiation …

Applications of artificial intelligence in stereotactic body radiation therapy

P Mancosu, N Lambri, I Castiglioni, D Dei… - Physics in Medicine …, 2022 - iopscience.iop.org
This topical review focuses on the applications of artificial intelligence (AI) tools to
stereotactic body radiation therapy (SBRT). The high dose per fraction and the limited …