Predicting cancer outcomes with radiomics and artificial intelligence in radiology

K Bera, N Braman, A Gupta, V Velcheti… - Nature reviews Clinical …, 2022 - nature.com
The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …

[HTML][HTML] Application of deep learning in breast cancer imaging

L Balkenende, J Teuwen, RM Mann - Seminars in Nuclear Medicine, 2022 - Elsevier
This review gives an overview of the current state of deep learning research in breast cancer
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …

Deep learning trained on hematoxylin and eosin tumor region of Interest predicts HER2 status and trastuzumab treatment response in HER2+ breast cancer

S Farahmand, AI Fernandez, FS Ahmed, DL Rimm… - Modern …, 2022 - nature.com
The current standard of care for many patients with HER2-positive breast cancer is
neoadjuvant chemotherapy in combination with anti-HER2 agents, based on HER2 …

Adoption of artificial intelligence in breast imaging: evaluation, ethical constraints and limitations

SE Hickman, GC Baxter, FJ Gilbert - British journal of cancer, 2021 - nature.com
Retrospective studies have shown artificial intelligence (AI) algorithms can match as well as
enhance radiologist's performance in breast screening. These tools can facilitate tasks not …

Deep learning in breast cancer imaging: A decade of progress and future directions

L Luo, X Wang, Y Lin, X Ma, A Tan… - IEEE Reviews in …, 2024 - ieeexplore.ieee.org
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …

Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using deep learning with integrative imaging, molecular and …

H Duanmu, PB Huang, S Brahmavar, S Lin… - … Image Computing and …, 2020 - Springer
Neoadjuvant chemotherapy is widely used to reduce tumor size to make surgical excision
manageable and to minimize distant metastasis. Assessing and accurately predicting …

Deep learning prediction of pathologic complete response in breast cancer using MRI and other clinical data: a systematic review

N Khan, R Adam, P Huang, T Maldjian, TQ Duong - Tomography, 2022 - mdpi.com
Breast cancer patients who have pathological complete response (pCR) to neoadjuvant
chemotherapy (NAC) are more likely to have better clinical outcomes. The ability to predict …

Artificial intelligence-enhanced breast MRI: applications in breast cancer primary treatment response assessment and prediction

RL Gullo, E Marcus, J Huayanay… - Investigative …, 2024 - journals.lww.com
Primary systemic therapy (PST) is the treatment of choice in patients with locally advanced
breast cancer and is nowadays also often used in patients with early-stage breast cancer …

Current status and future perspectives of artificial intelligence in magnetic resonance breast imaging

A Meyer-Bäse, L Morra, U Meyer-Bäse… - Contrast Media & …, 2020 - Wiley Online Library
Recent advances in artificial intelligence (AI) and deep learning (DL) have impacted many
scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well …

Dual-branch convolutional neural network based on ultrasound imaging in the early prediction of neoadjuvant chemotherapy response in patients with locally …

J Xie, H Shi, C Du, X Song, J Wei, Q Dong… - Frontiers in …, 2022 - frontiersin.org
The early prediction of a patient's response to neoadjuvant chemotherapy (NAC) in breast
cancer treatment is crucial for guiding therapy decisions. We aimed to develop a novel …