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Generalizable Deep Learning for the Detection of Incomplete and Complete Retinal Pigment Epithelium and Outer Retinal Atrophy: A MACUSTAR Report.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop a deep learning algorithm for detecting and quantifying incomplete retinal pigment epithelium and outer retinal atrophy (iRORA) and complete retinal pigment epithelium and outer retinal atrophy (cRORA...

A Novel Artificial Intelligence-Based Classification of Highly Myopic Eyes Based on Visual Function and Fundus Features.

Translational vision science & technology
PURPOSE: To develop a novel classification of highly myopic eyes using artificial intelligence (AI) and investigate its relationship with contrast sensitivity function (CSF) and fundus features.

Long-Term Rate of Optic Disc Rim Loss in Glaucoma Patients Measured From Optic Disc Photographs With a Deep Neural Network.

Translational vision science & technology
PURPOSE: This study uses deep neural network-generated rim-to-disc area ratio (RADAR) measurements and the disc damage likelihood scale (DDLS) to measure the rate of optic disc rim loss in a large cohort of glaucoma patients.

Streamlined Intraoperative Brain Tumor Classification and Molecular Subtyping in Stereotactic Biopsies Using Stimulated Raman Histology and Deep Learning.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Recent artificial intelligence algorithms aided intraoperative decision-making via stimulated Raman histology (SRH) during craniotomy. This study assesses deep learning algorithms for rapid intraoperative diagnosis from SRH images in small s...

Artificial intelligence classifies primary progressive aphasia from connected speech.

Brain : a journal of neurology
Neurodegenerative dementia syndromes, such as primary progressive aphasias (PPA), have traditionally been diagnosed based, in part, on verbal and non-verbal cognitive profiles. Debate continues about whether PPA is best divided into three variants an...

Early identification of patients at risk for iron-deficiency anemia using deep learning techniques.

American journal of clinical pathology
OBJECTIVES: Iron-deficiency anemia (IDA) is a common health problem worldwide, and up to 10% of adult patients with incidental IDA may have gastrointestinal cancer. A diagnosis of IDA can be established through a combination of laboratory tests, but ...

Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules.

JNCI cancer spectrum
BACKGROUND: Clinical utility data on pulmonary nodule (PN) risk stratification biomarkers are lacking. We aimed to determine the incremental predictive value and clinical utility of using an artificial intelligence (AI) radiomics-based computer-aided...

External validation of the SORG machine learning for 90-day and 1-year mortality in patients suffering from extremity metastatic disease in an European cohort of 174 patients.

Acta orthopaedica Belgica
Accurate survival prediction of patients with long-bone metastases is challenging, but important for optimizing treatment. The Skeletal Oncology Research Group (SORG) machine learning algorithm (MLA) has been previously developed and internally valid...