AIMC Topic: Sensitivity and Specificity

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AI-based smartphone apps for risk assessment of skin cancer need more evaluation and better regulation.

British journal of cancer
Smartphone applications ("apps") with artificial intelligence (AI) algorithms are increasingly used in healthcare. Widespread adoption of these apps must be supported by a robust evidence-base and app manufacturers' claims appropriately regulated. Cu...

Comparison of machine learning methods for prediction of osteoradionecrosis incidence in patients with head and neck cancer.

The British journal of radiology
OBJECTIVES: Mandible osteoradionecrosis (ORN) is one of the most severe toxicities in patients with head and neck cancer (HNC) undergoing radiotherapy (RT). The existing literature focuses on the correlation of mandible ORN and clinical and dosimetri...

Deep Learning in the Detection and Diagnosis of COVID-19 Using Radiology Modalities: A Systematic Review.

Journal of healthcare engineering
INTRODUCTION: The early detection and diagnosis of COVID-19 and the accurate separation of non-COVID-19 cases at the lowest cost and in the early stages of the disease are among the main challenges in the current COVID-19 pandemic. Concerning the nov...

Assessment of an Artificial Intelligence Algorithm for Detection of Intracranial Hemorrhage.

World neurosurgery
BACKGROUND: Immediate and accurate detection of intracranial hemorrhages (ICHs) is essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has the potential to provide this, but the assessment of these methods need...

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.

Deep learning with a convolutional neural network model to differentiate renal parenchymal tumors: a preliminary study.

Abdominal radiology (New York)
PURPOSE: With advancements in medical imaging, more renal tumors are detected early, but it remains a challenge for radiologists to accurately distinguish subtypes of renal parenchymal tumors. We aimed to establish a novel deep convolutional neural n...

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...

Metaheuristic-based Deep COVID-19 Screening Model from Chest X-Ray Images.

Journal of healthcare engineering
COVID-19 has affected the whole world drastically. A huge number of people have lost their lives due to this pandemic. Early detection of COVID-19 infection is helpful for treatment and quarantine. Therefore, many researchers have designed a deep lea...

Application of artificial intelligence in diagnosis of osteoporosis using medical images: a systematic review and meta-analysis.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Artificial intelligence (AI) is a potentially reliable assistant in the diagnosis of osteoporosis. This meta-analysis aims to assess the diagnostic accuracy of the AI-based systems using medical images. We searched PubMed and Web of Science from ince...