AIMC Topic: ROC Curve
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Performance Evaluation of a Deep Learning System for Differential Diagnosis of Lung Cancer With Conventional CT and FDG PET/CT Using Transfer Learning and Metadata.
Clinical nuclear medicine
Aug 1, 2021
PURPOSE: We aimed to evaluate the performance of a deep learning system for differential diagnosis of lung cancer with conventional CT and FDG PET/CT using transfer learning (TL) and metadata.
The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease.
Inflammatory bowel diseases
Jul 27, 2021
BACKGROUND: Although imaging, endoscopy, and inflammatory biomarkers are associated with future Crohn disease (CD) outcomes, common laboratory studies may also provide prognostic opportunities. We evaluated machine learning models incorporating routi...
Can a Deep-learning Model for the Automated Detection of Vertebral Fractures Approach the Performance Level of Human Subspecialists?
Clinical orthopaedics and related research
Jul 1, 2021
BACKGROUND: Vertebral fractures are the most common osteoporotic fractures in older individuals. Recent studies suggest that the performance of artificial intelligence is equal to humans in detecting osteoporotic fractures, such as fractures of the h...
An ensemble framework based on Deep CNNs architecture for glaucoma classification using fundus photography.
Mathematical biosciences and engineering : MBE
Jun 16, 2021
Glaucoma is a chronic ocular degenerative disease that can cause blindness if left untreated in its early stages. Deep Convolutional Neural Networks (Deep CNNs) and its variants have provided superior performance in glaucoma classification, segmentat...
Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.
Proceedings of the National Academy of Sciences of the United States of America
Jun 15, 2021
Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically...
Improving the delivery of palliative care through predictive modeling and healthcare informatics.
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, many patients who could benefit from PC do not receive it early enough or at all. We sought to address...
Automated model versus treating physician for predicting survival time of patients with metastatic cancer.
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: Being able to predict a patient's life expectancy can help doctors and patients prioritize treatments and supportive care. For predicting life expectancy, physicians have been shown to outperform traditional models that use only a few pred...
Machine-learning model to predict the cause of death using a stacking ensemble method for observational data.
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: Cause of death is used as an important outcome of clinical research; however, access to cause-of-death data is limited. This study aimed to develop and validate a machine-learning model that predicts the cause of death from the patient's l...
A deep learning approach to dental restoration classification from bitewing and periapical radiographs.
Quintessence international (Berlin, Germany : 1985)
Jun 9, 2021
OBJECTIVE: The aim of this study was to examine the success of deep learning-based convolutional neural networks (CNN) in the detection and differentiation of amalgam, composite resin, and metal-ceramic restorations from bitewing and periapical radio...
Radiographical assessment of tumour stroma and treatment outcomes using deep learning: a retrospective, multicohort study.
The Lancet. Digital health
Jun 1, 2021
BACKGROUND: The tumour stroma microenvironment plays an important part in disease progression and its composition can influence treatment response and outcomes. Histological evaluation of tumour stroma is limited by access to tissue, spatial heteroge...
Stomach
Chemotherapy, Adjuvant
Radiography
Progression-Free Survival
Disease-Free Survival
Proportional Hazards Models
ROC Curve
Predictive Value of Tests
Area Under Curve
Humans
Neural Networks, Computer
Male
Prognosis
Tomography, X-Ray Computed
Middle Aged
Retrospective Studies
Female
Deep Learning
Stomach Neoplasms
China
Biomarkers, Tumor
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