Deep learning in cancer diagnosis and prognosis prediction: a minireview on challenges, recent trends, and future directions
AB Tufail, YK Ma, MKA Kaabar… - … Methods in Medicine, 2021 - Wiley Online Library
Deep learning (DL) is a branch of machine learning and artificial intelligence that has been
applied to many areas in different domains such as health care and drug design. Cancer …
applied to many areas in different domains such as health care and drug design. Cancer …
An overview of artificial intelligence in oncology
E Farina, JJ Nabhen, MI Dacoregio, F Batalini… - Future science …, 2022 - Taylor & Francis
Cancer is associated with significant morbimortality globally. Advances in screening,
diagnosis, management and survivorship were substantial in the last decades, however …
diagnosis, management and survivorship were substantial in the last decades, however …
An inception‐ResNet deep learning approach to classify tumours in the ovary as benign and malignant
A Kodipalli, S Guha, S Dasar, T Ismail - Expert Systems, 2022 - Wiley Online Library
The classification of tumours into benign and malignant continues to date to be a very
relevant and significant research topic in the cancer research domain. With the advent of …
relevant and significant research topic in the cancer research domain. With the advent of …
Pre-trained deep learning models for brain MRI image classification
S Krishnapriya, Y Karuna - Frontiers in Human Neuroscience, 2023 - frontiersin.org
Brain tumors are serious conditions caused by uncontrolled and abnormal cell division.
Tumors can have devastating implications if not accurately and promptly detected. Magnetic …
Tumors can have devastating implications if not accurately and promptly detected. Magnetic …
The brain tumor segmentation (brats-mets) challenge 2023: Brain metastasis segmentation on pre-treatment mri
The translation of AI-generated brain metastases (BM) segmentation into clinical practice
relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS …
relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS …
Brain metastasis detection using machine learning: a systematic review and meta-analysis
Background Accurate detection of brain metastasis (BM) is important for cancer patients. We
aimed to systematically review the performance and quality of machine-learning-based BM …
aimed to systematically review the performance and quality of machine-learning-based BM …
A review on the recent applications of deep learning in predictive drug toxicological studies
Drug toxicity prediction is an important step in ensuring patient safety during drug design
studies. While traditional preclinical studies have historically relied on animal models to …
studies. While traditional preclinical studies have historically relied on animal models to …
Small ship detection of SAR images based on optimized feature pyramid and sample augmentation
Synthetic aperture radar images have become the latest high-resolution imaging equipment,
which can monitor the Earth 24 ha day. More and more deep-learning technologies are …
which can monitor the Earth 24 ha day. More and more deep-learning technologies are …
Automatic detection of mesiodens on panoramic radiographs using artificial intelligence
This study aimed to develop an artificial intelligence model that can detect mesiodens on
panoramic radiographs of various dentition groups. Panoramic radiographs of 612 patients …
panoramic radiographs of various dentition groups. Panoramic radiographs of 612 patients …
Artificial intelligence in multiparametric magnetic resonance imaging: A review
Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …