AIMC Topic: ROC Curve
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Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma.
BMC cancer
Jun 1, 2020
BACKGROUND: Early radiation-induced temporal lobe injury (RTLI) diagnosis in nasopharyngeal carcinoma (NPC) is clinically challenging, and prediction models of RTLI are lacking. Hence, we aimed to develop radiomic models for early detection of RTLI.
Humans
Machine Learning
Algorithms
Retrospective Studies
ROC Curve
Longitudinal Studies
Magnetic Resonance Imaging
Brain Injuries
Predictive Value of Tests
Female
Adult
Male
Middle Aged
Aftercare
Nasopharyngeal Carcinoma
Models, Biological
Nasopharyngeal Neoplasms
Image Interpretation, Computer-Assisted
Temporal Lobe
Radiation Injuries
CRISPRpred(SEQ): a sequence-based method for sgRNA on target activity prediction using traditional machine learning.
BMC bioinformatics
Jun 1, 2020
BACKGROUND: The latest works on CRISPR genome editing tools mainly employs deep learning techniques. However, deep learning models lack explainability and they are harder to reproduce. We were motivated to build an accurate genome editing tool using ...
Effect of congenital adrenal hyperplasia treated by glucocorticoids on plasma metabolome: a machine-learning-based analysis.
Scientific reports
Jun 1, 2020
BACKGROUND: Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency leads to impaired cortisol biosynthesis. Treatment includes glucocorticoid supplementation. We studied the specific metabolomics signatures in CAH patients using two di...
A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance.
European radiology
May 30, 2020
OBJECTIVES: To develop a deep learning algorithm for automated detection and localization of intracranial aneurysms on time-of-flight MR angiography and evaluate its diagnostic performance.
Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography.
Occupational and environmental medicine
May 29, 2020
OBJECTIVES: To investigate the potential of deep learning in assessing pneumoconiosis depicted on digital chest radiographs and to compare its performance with certified radiologists.
A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy.
Breast cancer research : BCR
May 28, 2020
BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and va...
Predicting Survival After Extracorporeal Membrane Oxygenation by Using Machine Learning.
The Annals of thoracic surgery
May 23, 2020
BACKGROUND: Venoarterial (VA) extracorporeal membrane oxygenation (ECMO) undoubtedly saves many lives, but it is associated with a high degree of patient morbidity, mortality, and resource use. This study aimed to develop a machine learning algorithm...
Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2.
Ophthalmology
May 21, 2020
PURPOSE: To develop deep learning models for detecting reticular pseudodrusen (RPD) using fundus autofluorescence (FAF) images or, alternatively, color fundus photographs (CFP) in the context of age-related macular degeneration (AMD).
The development an artificial intelligence algorithm for early sepsis diagnosis in the intensive care unit.
International journal of medical informatics
May 21, 2020
BACKGROUND: Severe sepsis and septic shock are still the leading causes of death in Intensive Care Units (ICUs), and timely diagnosis is crucial for treatment outcomes. The progression of electronic medical records (EMR) offers the possibility of sto...
Non - invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps.
Computer methods in biomechanics and biomedical engineering
May 20, 2020
Cardiovascular diseases (CVD) and strokes produce immense health and economic burdens globally. Coronary Artery Disease (CAD) is the most common type of cardiovascular disease. Coronary Angiography, which is an invasive approach for detection and tre...
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