[HTML][HTML] The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges
Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …
Current applications and future impact of machine learning in radiology
Recent advances and future perspectives of machine learning techniques offer promising
applications in medical imaging. Machine learning has the potential to improve different …
applications in medical imaging. Machine learning has the potential to improve different …
Artificial intelligence in cancer imaging: clinical challenges and applications
Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered
data with nuanced decision making. Cancer offers a unique context for medical decisions …
data with nuanced decision making. Cancer offers a unique context for medical decisions …
The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review
K Hung, C Montalvao, R Tanaka… - Dentomaxillofacial …, 2020 - academic.oup.com
Objectives: To investigate the current clinical applications and diagnostic performance of
artificial intelligence (AI) in dental and maxillofacial radiology (DMFR). Methods: Studies …
artificial intelligence (AI) in dental and maxillofacial radiology (DMFR). Methods: Studies …
[HTML][HTML] Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology
Medical image processing and analysis (also known as Radiomics) is a rapidly growing
discipline that maps digital medical images into quantitative data, with the end goal of …
discipline that maps digital medical images into quantitative data, with the end goal of …
Radiomics: from qualitative to quantitative imaging
W Rogers, S Thulasi Seetha… - The British journal of …, 2020 - academic.oup.com
Historically, medical imaging has been a qualitative or semi-quantitative modality. It is
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …
Artificial intelligence in cancer research: trends, challenges and future directions
AM Sebastian, D Peter - Life, 2022 - mdpi.com
The World Health Organization (WHO), in their 2022 report, identified cancer as one of the
leading causes of death, accounting for about 16% of deaths worldwide. The Cancer …
leading causes of death, accounting for about 16% of deaths worldwide. The Cancer …
Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective
Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases,
such as skin, breast, and lung cancer. AI is an advanced form of technology that uses …
such as skin, breast, and lung cancer. AI is an advanced form of technology that uses …
[HTML][HTML] Radiomics and artificial intelligence in lung cancer screening
F Binczyk, W Prazuch, P Bozek… - Translational lung cancer …, 2021 - ncbi.nlm.nih.gov
Lung cancer is responsible for more fatalities than any other cancer worldwide, with 1.76
million associated deaths reported in 2018. The key issue in the fight against this disease is …
million associated deaths reported in 2018. The key issue in the fight against this disease is …
Highly accurate model for prediction of lung nodule malignancy with CT scans
Computed tomography (CT) examinations are commonly used to predict lung nodule
malignancy in patients, which are shown to improve noninvasive early diagnosis of lung …
malignancy in patients, which are shown to improve noninvasive early diagnosis of lung …