AIMC Topic: Sensitivity and Specificity
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A Novel Machine Learning-derived Radiomic Signature of the Whole Lung Differentiates Stable From Progressive COVID-19 Infection: A Retrospective Cohort Study.
Journal of thoracic imaging
Nov 1, 2020
OBJECTIVE: This study aimed to use the radiomics signatures of a machine learning-based tool to evaluate the prognosis of patients with coronavirus disease 2019 (COVID-19) infection.
[Discrimination of lung cancer and adjacent normal tissues based on permittivity by optimized probabilistic neural network].
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Oct 30, 2020
OBJECTIVE: To propose a probabilistic neural network classification method optimized by simulated annealing algorithm (SA-PNN) to discriminate lung cancer and adjacent normal tissues based on permittivity.
Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning.
Chemical Society reviews
Oct 19, 2020
Many problems exist within the myriad of currently employed screening and diagnostic methods. Further, an incredibly wide variety of procedures are used to identify an even greater number of diseases which exist in the world. There is a definite unme...
Ultrasonographic Thyroid Nodule Classification Using a Deep Convolutional Neural Network with Surgical Pathology.
Journal of digital imaging
Oct 1, 2020
Ultrasonography with fine-needle aspiration biopsy is commonly used to detect thyroid cancer. However, thyroid ultrasonography is prone to subjective interpretations and interobserver variabilities. The objective of this study was to develop a thyroi...
Using deep-learning algorithms to classify fetal brain ultrasound images as normal or abnormal.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Oct 1, 2020
OBJECTIVES: To evaluate the feasibility of using deep-learning algorithms to classify as normal or abnormal sonographic images of the fetal brain obtained in standard axial planes.
[Application of artificial intelligence combined with multi-parametric MRI in the early diagnosis of prostate cancer].
Zhonghua nan ke xue = National journal of andrology
Sep 1, 2020
OBJECTIVE: To explore the value of artificial intelligence combined with multi-parametric MRI (AI-mpMRI) in the early diagnosis of prostate cancer.
A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019.
Diagnostic and interventional radiology (Ankara, Turkey)
Sep 1, 2020
The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of ...
Colon capsule endoscopy versus CT colonography after incomplete colonoscopy. Application of artificial intelligence algorithms to identify complete colonic investigations.
United European gastroenterology journal
Aug 1, 2020
BACKGROUND: Guidelines suggest computed tomography colonography (CTC) following incomplete optical colonoscopy (OC). Colon capsule endoscopies (CCE) have been suggested as an alternative, although completion rates have been unsatisfactory. Introducti...
Deep Convolutional Neural Network-Based Diagnosis of Anterior Cruciate Ligament Tears: Performance Comparison of Homogenous Versus Heterogeneous Knee MRI Cohorts With Different Pulse Sequence Protocols and 1.5-T and 3-T Magnetic Field Strengths.
Investigative radiology
Aug 1, 2020
OBJECTIVES: The aim of this study was to clinically validate a Deep Convolutional Neural Network (DCNN) for the detection of surgically proven anterior cruciate ligament (ACL) tears in a large patient cohort and to analyze the effect of magnetic reso...
Validating clinical threshold values for a dashboard view of the compensatory reserve measurement for hemorrhage detection.
The journal of trauma and acute care surgery
Aug 1, 2020
BACKGROUND: Compensatory reserve measurement (CRM) is a novel noninvasive monitoring technology designed to assess physiologic reserve using feature interrogation of arterial pulse waveforms. This study was conducted to validate clinically relevant C...
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