A systematic review of artificial intelligence techniques in cancer prediction and diagnosis
Artificial intelligence has aided in the advancement of healthcare research. The availability
of open-source healthcare statistics has prompted researchers to create applications that aid …
of open-source healthcare statistics has prompted researchers to create applications that aid …
Medical imaging and nuclear medicine: a Lancet Oncology Commission
The diagnosis and treatment of patients with cancer requires access to imaging to ensure
accurate management decisions and optimal outcomes. Our global assessment of imaging …
accurate management decisions and optimal outcomes. Our global assessment of imaging …
Comparison of deep learning approaches to predict COVID-19 infection
TB Alakus, I Turkoglu - Chaos, Solitons & Fractals, 2020 - Elsevier
The SARS-CoV2 virus, which causes COVID-19 (coronavirus disease) has become a
pandemic and has expanded all over the world. Because of increasing number of cases day …
pandemic and has expanded all over the world. Because of increasing number of cases day …
Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival
A Moncada-Torres, MC van Maaren, MP Hendriks… - Scientific reports, 2021 - nature.com
Abstract Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in
oncology. Recently, several machine learning (ML) techniques have been adapted for this …
oncology. Recently, several machine learning (ML) techniques have been adapted for this …
Brain tumor/mass classification framework using magnetic-resonance-imaging-based isolated and developed transfer deep-learning model
With the advancement in technology, machine learning can be applied to diagnose the
mass/tumor in the brain using magnetic resonance imaging (MRI). This work proposes a …
mass/tumor in the brain using magnetic resonance imaging (MRI). This work proposes a …
Automated detection and forecasting of covid-19 using deep learning techniques: A review
A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Neurocomputing, 2024 - Elsevier
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Dynamic routing between capsules
A capsule is a group of neurons whose activity vector represents the instantiation
parameters of a specific type of entity such as an object or object part. We use the length of …
parameters of a specific type of entity such as an object or object part. We use the length of …
The role of artificial intelligence in fighting the COVID-19 pandemic
The first few months of 2020 have profoundly changed the way we live our lives and carry
out our daily activities. Although the widespread use of futuristic robotaxis and self-driving …
out our daily activities. Although the widespread use of futuristic robotaxis and self-driving …
Pan-cancer landscape of T-cell exhaustion heterogeneity within the tumor microenvironment revealed a progressive roadmap of hierarchical dysfunction associated …
Background T cells form the major component of anti-tumor immunity. A deeper
understanding of T cell exhaustion (TEX) heterogeneity within the tumor microenvironment …
understanding of T cell exhaustion (TEX) heterogeneity within the tumor microenvironment …
Machine learning techniques for personalised medicine approaches in immune-mediated chronic inflammatory diseases: applications and challenges
In the past decade, the emergence of machine learning (ML) applications has led to
significant advances towards implementation of personalised medicine approaches for …
significant advances towards implementation of personalised medicine approaches for …