Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review
A Ghasemi, S Hashtarkhani, DL Schwartz… - Cancer …, 2024 - Wiley Online Library
With the advances in artificial intelligence (AI), data‐driven algorithms are becoming
increasingly popular in the medical domain. However, due to the nonlinear and complex …
increasingly popular in the medical domain. However, due to the nonlinear and complex …
The role of AI in breast cancer lymph node classification: a comprehensive review
Simple Summary Breast cancer affects countless women worldwide, and detecting the
spread of cancer to the lymph nodes is crucial for determining the best course of treatment …
spread of cancer to the lymph nodes is crucial for determining the best course of treatment …
Harnessing fusion modeling for enhanced breast cancer classification through interpretable artificial intelligence and in-depth explanations
Abstract Integrating Artificial Intelligence (AI) into healthcare has shown tremendous promise
in several domains, such as prediction, decision-making, and diagnosis. Nevertheless, the …
in several domains, such as prediction, decision-making, and diagnosis. Nevertheless, the …
A comparative performance assessment of artificial intelligence based classifiers and optimized feature reduction technique for breast cancer diagnosis
S Batool, S Zainab - Computers in Biology and Medicine, 2024 - Elsevier
Breast cancer (BC) is a catastrophic global health concern that causes numerous fatalities
worldwide. Early detection of breast cancer may mitigate death rates; however, the …
worldwide. Early detection of breast cancer may mitigate death rates; however, the …
Identification of sentinel lymph node macrometastasis in breast cancer by deep learning based on clinicopathological characteristics
D Zhang, M Svensson, P Edén, L Dihge - Scientific Reports, 2024 - nature.com
The axillary lymph node status remains an important prognostic factor in breast cancer, and
nodal staging using sentinel lymph node biopsy (SLNB) is routine. Randomized clinical …
nodal staging using sentinel lymph node biopsy (SLNB) is routine. Randomized clinical …
XML‐LightGBMDroid: A self‐driven interactive mobile application utilizing explainable machine learning for breast cancer diagnosis
KM Mohi Uddin, N Biswas, ST Rikta… - Engineering …, 2023 - Wiley Online Library
Nowadays, breast cancer detection and diagnosis are done using machine learning
algorithms. It can enhance cancer understanding and help in treatment selection and …
algorithms. It can enhance cancer understanding and help in treatment selection and …
Machine-learning methods in detecting breast cancer and related therapeutic issues: a review
A Jafari - Computer Methods in Biomechanics and Biomedical …, 2024 - Taylor & Francis
ABSTRACT In 2020, the World Health Organization reported that breast cancer resulted in
the deaths of 685,000 people worldwide, with 2.3 million women diagnosed with the …
the deaths of 685,000 people worldwide, with 2.3 million women diagnosed with the …
Advances in the application of computational pathology in diagnosis, immunomicroenvironment recognition, and immunotherapy evaluation of breast cancer: A …
J Luo, X Li, KL Wei, G Chen, DD Xiong - Journal of Cancer Research and …, 2023 - Springer
Background Breast cancer (BC) is a prevalent and highly lethal malignancy affecting women
worldwide. Immunotherapy has emerged as a promising therapeutic strategy for BC, offering …
worldwide. Immunotherapy has emerged as a promising therapeutic strategy for BC, offering …
[HTML][HTML] From Bits to Atoms: Machine Learning and Nanotechnology for Cancer Therapy
Cancer therapy has seen significant advancements in recent years, with the integration of
machine learning and nanotechnology emerging as a promising new approach to improve …
machine learning and nanotechnology emerging as a promising new approach to improve …
Introducción al machine learning en Senología
EA Ferrara - Revista de Senología y Patología Mamaria, 2023 - Elsevier
Abstract Machine Learning or Statistical Learning is a concept belonging to the field of
Computer Science that refers to the ability of machines to build mathematical models with …
Computer Science that refers to the ability of machines to build mathematical models with …