AIMC Topic: Prognosis

Clear Filters Showing 2081 to 2090 of 3837 articles

[Artificial intelligence, radiomics and pathomics to predict response and survival of patients treated with radiations].

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Artificial intelligence approaches in medicine are more and more used and are extremely promising due to the growing number of data produced and the variety of data they allow to exploit. Thus, the computational analysis of medical images in particul...

Predicting survival in heart failure: a risk score based on machine-learning and change point algorithm.

Clinical research in cardiology : official journal of the German Cardiac Society
OBJECTIVE: Machine learning (ML) algorithm can improve risk prediction because ML can select features and segment continuous variables effectively unbiased. We generated a risk score model for mortality with ML algorithms in East-Asian patients with ...

DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data.

Genome medicine
Multi-omics data are good resources for prognosis and survival prediction; however, these are difficult to integrate computationally. We introduce DeepProg, a novel ensemble framework of deep-learning and machine-learning approaches that robustly pre...

Deep Learning on MRI Images for Diagnosis of Lung Cancer Spinal Bone Metastasis.

Contrast media & molecular imaging
This paper aimed to explore the adoption of deep learning algorithms in lung cancer spinal bone metastasis diagnosis. Comprehensive analysis was carried out with the aid of AdaBoost algorithm and Chan-Vese (CV) algorithm. 87 patients with lung cancer...

Convolutional Neural Network of Multiparametric MRI Accurately Detects Axillary Lymph Node Metastasis in Breast Cancer Patients With Pre Neoadjuvant Chemotherapy.

Clinical breast cancer
BACKGROUND: Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the ma...

Prediction model for thyrotoxic atrial fibrillation: a retrospective study.

BMC endocrine disorders
BACKGROUND: Thyrotoxic atrial fibrillation (TAF) is a recognized significant complication of hyperthyroidism. Early identification of the individuals predisposed to TAF would improve thyrotoxic patients' management. However, to our knowledge, an inst...

CRP (C-Reactive Protein) in Outcome Prediction After Subarachnoid Hemorrhage and the Role of Machine Learning.

Stroke
BACKGROUND AND PURPOSE: Outcome prediction after aneurysmal subarachnoid hemorrhage (aSAH) is challenging. CRP (C-reactive protein) has been reported to be associated with outcome, but it is unclear if this is independent of other predictors and appl...

Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence.

BMJ open
INTRODUCTION: The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias ASsessment Tool (PROBAST) were both published to improve the reporting and criti...

A comparative study of perioperative and survival outcomes of robot-assisted radical cystectomy in patients over 80 and under 80 years old.

World journal of surgical oncology
BACKGROUND: Radical cystectomy (RC) is the standard treatment for bladder cancer, but the safety and efficacy of this treatment for elderly people need to be considered. We compare perioperative data and survival outcomes between elderly (≥80 years) ...