A5046760392- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Advanced Radiotherapy Techniques
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Radiation Dose and Imaging
- Prostate Cancer Diagnosis and Treatment
- AI in cancer detection
- Colorectal Cancer Screening and Detection
- Radiation Therapy and Dosimetry
- Medical Imaging Techniques and Applications
- Gastrointestinal disorders and treatments
- Advanced X-ray and CT Imaging
- Prostate Cancer Treatment and Research
- Artificial Intelligence in Healthcare and Education
- Inflammatory Bowel Disease
- Lung Cancer Diagnosis and Treatment
- Colorectal Cancer Surgical Treatments
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Gastric Cancer Management and Outcomes
- Gallbladder and Bile Duct Disorders
- Pancreatic and Hepatic Oncology Research
- Hepatocellular Carcinoma Treatment and Prognosis
- Liver Disease Diagnosis and Treatment
Champalimaud Foundation
2016-2025
Royal Marsden Hospital
2008-2025
Memorial Sloan Kettering Cancer Center
2024
Universidade de São Paulo
2024
Royal Marsden NHS Foundation Trust
2022-2024
Foundation for Research and Technology Hellas
2012-2022
Karolinska Institutet
2011-2022
The General Hospital of Heraklion "Venizeleio-Pananio"
2001-2022
Institute of Cancer Research
2022
FORTH Institute of Electronic Structure and Laser
2022
Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology improve diagnosis, prognostication, clinical decision support, with goal delivering precision medicine. The authors provide a practical approach for successfully implementing radiomic workflow planning conceptualization through manuscript writing. Applications in typically are either classification tasks that involve computing probability sample belonging category, such as benign...
Abstract Purpose To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research of radiomics studies. Methods We conducted an online modified Delphi study with group international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members identify the items be voted; Stage#3, four rounds exercise by panelists determine eligible for METRICS their weights. The...
COVID-19 has led to an unprecedented healthcare crisis with millions of infected people across the globe often pushing infrastructures, workers and entire economies beyond their limits. The scarcity testing kits, even in developed countries, extensive research efforts towards alternative solutions high sensitivity. Chest radiological imaging paired artificial intelligence (AI) can offer significant advantages diagnosis novel coronavirus patients. To this end, transfer learning techniques are...
“Just Accepted” papers have undergone full peer review and been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, proof before it is published its final version. Please note that during production of the copyedited article, errors may be discovered which could affect content. Purpose To assess impact scanner manufacturer scan protocol on performance deep learning models to classify prostate cancer (PCa) aggressiveness biparametric...
Introduction: Innovations in 3D spatial technology and augmented reality imaging driven by digital high-tech industrial science have accelerated experimental advances breast cancer the development of medical procedures aimed to reduce invasiveness. Presentation case: A 57-year-old post-menopausal woman presented with screen-detected left-sided cancer. After undergoing all staging pre-operative studies patient was proposed for conservative surgery tumor localization. During surgery, an...
Prostate cancer is one of the most common forms globally, affecting roughly in every eight men according to American Cancer Society. Although survival rate for prostate significantly high given very incidence rate, there an urgent need improve and develop new clinical aid systems help detect treat a timely manner. In this retrospective study, our contributions are twofold: First, we perform comparative unified study different commonly used segmentation models gland zone (peripheral...
Abstract Background To build machine learning predictive models for surgical risk assessment of extracapsular extension (ECE) in patients with prostate cancer (PCa) before radical prostatectomy; and to compare the use decision curve analysis (DCA) receiver operating characteristic (ROC) metrics selecting input feature combinations models. Methods This retrospective observational study included two independent data sets: 139 participants from a single institution (training), 55 15 other...
The prognostic value of the dynamic contrast-enhanced (DCE) MRI perfusion and its histogram analysis-derived metrics is not well established for high-grade glioma (HGG) patients. aim this prospective study was to investigate DCE transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular (ve), reverse constant (kep), initial area under gadolinium concentration time curve (IAUGC) as predictors progression-free (PFS) overall survival (OS) in HGG patients.Sixty-nine...