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MRI-Based Deep-Learning Method for Determining Glioma Promoter Methylation Status.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: () promoter methylation confers an improved prognosis and treatment response in gliomas. We developed a deep learning network for determining promoter methylation status using T2 weighted Images (T2WI) only.

Epidemiological Surveillance of the Impact of the COVID-19 Pandemic on Stroke Care Using Artificial Intelligence.

Stroke
BACKGROUND AND PURPOSE: The degree to which the coronavirus disease 2019 (COVID-19) pandemic has affected systems of care, in particular, those for time-sensitive conditions such as stroke, remains poorly quantified. We sought to evaluate the impact ...

Clinical Features of Emergency Department Patients from Early COVID-19 Pandemic that Predict SARS-CoV-2 Infection: Machine-learning Approach.

The western journal of emergency medicine
INTRODUCTION: Within a few months coronavirus disease 2019 (COVID-19) evolved into a pandemic causing millions of cases worldwide, but it remains challenging to diagnose the disease in a timely fashion in the emergency department (ED). In this study ...

Clinical presentation of COVID-19 - a model derived by a machine learning algorithm.

Journal of integrative bioinformatics
COVID-19 pandemic has flooded all triage stations, making it difficult to carefully select those most likely infected. Data on total patients tested, infected, and hospitalized is fragmentary making it difficult to easily select those most likely to ...

Semi-automated tracking of pain in critical care patients using artificial intelligence: a retrospective observational study.

Scientific reports
Monitoring the pain intensity in critically ill patients is crucial because intense pain can cause adverse events, including poor survival rates; however, continuous pain evaluation is difficult. Vital signs have traditionally been considered ineffec...

Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value.

BMC medicine
BACKGROUND: Artificial intelligence (AI) in diagnostic radiology is undergoing rapid development. Its potential utility to improve diagnostic performance for cardiopulmonary events is widely recognized, but the accuracy and precision have yet to be d...

Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study.

PloS one
BACKGROUND: Osteoporosis has increased and developed into a serious public health concern worldwide. Despite the high prevalence, osteoporosis is silent before major fragility fracture and the osteoporosis screening rate is low. Abdomen-pelvic CT (AP...

Clinical implementation of deep learning contour autosegmentation for prostate radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Artificial intelligence advances have stimulated a new generation of autosegmentation, however clinical evaluations of these algorithms are lacking. This study assesses the clinical utility of deep learning-based autosegmentat...

Artificial intelligence prediction model for overall survival of clear cell renal cell carcinoma based on a 21-gene molecular prognostic score system.

Aging
We developed and validated a new prognostic model for predicting the overall survival in clear cell renal cell carcinoma (ccRCC) patients. In this study, artificial intelligence (AI) algorithms including random forest and neural network were trained ...

Deep learning systems detect dysplasia with human-like accuracy using histopathology and probe-based confocal laser endomicroscopy.

Scientific reports
Probe-based confocal laser endomicroscopy (pCLE) allows for real-time diagnosis of dysplasia and cancer in Barrett's esophagus (BE) but is limited by low sensitivity. Even the gold standard of histopathology is hindered by poor agreement between path...