AIMC Topic: Sensitivity and Specificity

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Domain adaptation and self-supervised learning for surgical margin detection.

International journal of computer assisted radiology and surgery May 6, 2021
PURPOSE: One in five women who undergo breast conserving surgery will need a second revision surgery due to remaining tumor. The iKnife is a mass spectrometry modality that produces real-time margin information based on the metabolite signatures in s...
Breast Neoplasms Area Under Curve Skin Breast Mastectomy Supervised Machine Learning Calibration Operating Rooms Skin Neoplasms Carcinoma, Basal Cell Reproducibility of Results Sensitivity and Specificity Humans Machine Learning Stochastic Processes Algorithms Margins of Excision Female Mastectomy, Segmental
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Artificial intelligence assists identifying malignant versus benign liver lesions using contrast-enhanced ultrasound.

Journal of gastroenterology and hepatology May 5, 2021
BACKGROUND AND AIM: This study aims to construct a strategy that uses assistance from artificial intelligence (AI) to assist radiologists in the identification of malignant versus benign focal liver lesions (FLLs) using contrast-enhanced ultrasound (...
Sensitivity and Specificity Humans Ultrasonography Liver Neoplasms Artificial Intelligence Contrast Media Magnetic Resonance Imaging
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AI-based pathology predicts origins for cancers of unknown primary.

Nature May 5, 2021
Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the primary anatomical site of tumour origin cannot be determined. This poses a considerable challenge, as modern therapeutics are predominantly specific to the primar...
Computer Simulation Neoplasm Metastasis Female Reproducibility of Results Neoplasms, Unknown Primary Humans Sensitivity and Specificity Artificial Intelligence Male Cohort Studies Workflow
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Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study.

Radiology May 4, 2021
Background The interpretation of radiographs suffers from an ever-increasing workload in emergency and radiology departments, while missed fractures represent up to 80% of diagnostic errors in the emergency department. Purpose To assess the performan...
Retrospective Studies Female Reproducibility of Results Aged Humans Artificial Intelligence Physicians Cross-Sectional Studies Male Middle Aged Adolescent Fractures, Bone Aged, 80 and over Young Adult Adult Sensitivity and Specificity Emergency Service, Hospital Radiologists Radiographic Image Interpretation, Computer-Assisted
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Development and Validation of a Deep Learning Model Using Convolutional Neural Networks to Identify Scaphoid Fractures in Radiographs.

JAMA network open May 3, 2021
IMPORTANCE: Scaphoid fractures are the most common carpal fracture, but as many as 20% are not visible (ie, occult) in the initial injury radiograph; untreated scaphoid fractures can lead to degenerative wrist arthritis and debilitating pain, detrime...
Fractures, Bone Adult Area Under Curve Sensitivity and Specificity Radiography Humans Deep Learning Scaphoid Bone ROC Curve
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Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

JAMA network open May 3, 2021
IMPORTANCE: A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of RO...
Retinopathy of Prematurity Infant, Newborn Sensitivity and Specificity Male Deep Learning Humans Female Area Under Curve Infant, Premature Neonatal Screening Ophthalmoscopy
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Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma.

Clinical radiology May 1, 2021
AIM: To investigate machine learning based models combining clinical, radiomic, and molecular information to distinguish between early true progression (tPD) and pseudoprogression (psPD) in patients with glioblastoma.
Diagnosis, Differential Reproducibility of Results Predictive Value of Tests Aged Glioblastoma Young Adult Adolescent Image Enhancement Image Interpretation, Computer-Assisted Adult Treatment Outcome Chemoradiotherapy Sensitivity and Specificity Contrast Media Machine Learning Brain Neoplasms Magnetic Resonance Imaging Humans Brain Male Retrospective Studies Middle Aged Female
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An artificial intelligence deep learning model for identification of small bowel obstruction on plain abdominal radiographs.

The British journal of radiology Apr 27, 2021
OBJECTIVES: Small bowel obstruction is a common surgical emergency which can lead to bowel necrosis, perforation and death. Plain abdominal X-rays are frequently used as a first-line test but the availability of immediate expert radiological review i...
Humans Female Aged Adult Feasibility Studies Sensitivity and Specificity Intestinal Obstruction Male Intestine, Small Middle Aged Radiography, Abdominal Deep Learning
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A fused-image-based approach to detect obstructive sleep apnea using a single-lead ECG and a 2D convolutional neural network.

PloS one Apr 26, 2021
Obstructive sleep apnea (OSA) is a common chronic sleep disorder that disrupts breathing during sleep and is associated with many other medical conditions, including hypertension, coronary heart disease, and depression. Clinically, the standard for d...
Image Processing, Computer-Assisted Electrocardiography Sleep Apnea, Obstructive Automation Humans Neural Networks, Computer Databases, Factual Sensitivity and Specificity
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Prediction of COVID-19 with Computed Tomography Images using Hybrid Learning Techniques.

Disease markers Apr 22, 2021
Reverse Transcription Polymerase Chain Reaction (RT-PCR) used for diagnosing COVID-19 has been found to give low detection rate during early stages of infection. Radiological analysis of CT images has given higher prediction rate when compared to RT-...
Decision Trees Humans Sensitivity and Specificity Pneumonia Machine Learning Lung Bayes Theorem COVID-19 Community-Acquired Infections Case-Control Studies Tomography, X-Ray Computed Models, Statistical
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