We aimed to assess the use of automatic machine learning (AutoML) algorithm based on magnetic resonance (MR) image data to assign prediction scores to patients with nasopharyngeal carcinoma (NPC). We also aimed to develop a 4-group classification system for NPC, superior to the current clinical staging system. Between January 2010 and January 2013, 792 patients with recent diagnosis of NPC, who had MR image data, were enrolled in the study. The AutoML algorithm was used and all statistical analyses were based on the 10-fold test. Primary endpoints included the probabilities of overall survival (OS), distant metastasis-free survival (DMFS), and local-region relapse-free survival (LRFS), and their sum was recorded as the final voting score, r...
Background: We aimed to identify a magnetic resonance imaging (MRI)-based model for assessment of th...
In this thesis different machine learning algorithms have been utilised to predict treatment outcome...
In this thesis, we presented the design steps for developing new, reliable, and cost-effective diagn...
Background: The Cox proportional hazards (CPH) model is the most commonly used statistical method fo...
Nasopharyngeal cancer (NPC) has a unique histopathology compared with other head and neck cancers. I...
Abstract: Machine learning is a branch of artifi cial intelligence that employs a variety of statist...
More than 750 000 women in Italy are surviving a diagnosis of breast cancer. A large body of li...
Background: Induction chemotherapy (ICT) plus concurrent chemoradiotherapy (CCRT) and CCRT alone wer...
The purpose of this study was to determine the predictive power for treatment outcome of a machine-l...
Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The ...
Purpose. Quantitative lymph node burden has been demonstrated to be a critical prognosticator in var...
Purpose: Non-small-cell lung cancer (NSCLC) shows a high incidence of brain metastases (BM). Early d...
With an estimated 1.4 million cancer diagnosis worldwide and the increasing death of cancer patients...
The survival rate of breast cancer prediction has been a significant issue for researchers. Nowadays...
AbstractCancer has been characterized as a heterogeneous disease consisting of many different subtyp...
Background: We aimed to identify a magnetic resonance imaging (MRI)-based model for assessment of th...
In this thesis different machine learning algorithms have been utilised to predict treatment outcome...
In this thesis, we presented the design steps for developing new, reliable, and cost-effective diagn...
Background: The Cox proportional hazards (CPH) model is the most commonly used statistical method fo...
Nasopharyngeal cancer (NPC) has a unique histopathology compared with other head and neck cancers. I...
Abstract: Machine learning is a branch of artifi cial intelligence that employs a variety of statist...
More than 750 000 women in Italy are surviving a diagnosis of breast cancer. A large body of li...
Background: Induction chemotherapy (ICT) plus concurrent chemoradiotherapy (CCRT) and CCRT alone wer...
The purpose of this study was to determine the predictive power for treatment outcome of a machine-l...
Cancer has been characterized as a heterogeneous disease consisting of many different subtypes. The ...
Purpose. Quantitative lymph node burden has been demonstrated to be a critical prognosticator in var...
Purpose: Non-small-cell lung cancer (NSCLC) shows a high incidence of brain metastases (BM). Early d...
With an estimated 1.4 million cancer diagnosis worldwide and the increasing death of cancer patients...
The survival rate of breast cancer prediction has been a significant issue for researchers. Nowadays...
AbstractCancer has been characterized as a heterogeneous disease consisting of many different subtyp...
Background: We aimed to identify a magnetic resonance imaging (MRI)-based model for assessment of th...
In this thesis different machine learning algorithms have been utilised to predict treatment outcome...
In this thesis, we presented the design steps for developing new, reliable, and cost-effective diagn...