AIMC Topic:
ROC Curve
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Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer.
Cancer research and treatment
Jun 15, 2021
PURPOSE: Machine learning (ML) is a strong candidate for making accurate predictions, as we can use large amount of data with powerful computational algorithms. We developed a ML based model to predict survival of patients with colorectal cancer (CRC...
Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.
Nature biomedical engineering
Jun 15, 2021
Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidn...
Metadata
Photography
Body Weight
Retina
Body Height
Image Interpretation, Computer-Assisted
Body Mass Index
Area Under Curve
Fundus Oculi
Middle Aged
Disease Progression
Deep Learning
ROC Curve
Blood Glucose
Neural Networks, Computer
Humans
Diabetes Mellitus, Type 2
Prospective Studies
Renal Insufficiency, Chronic
Female
Glomerular Filtration Rate
Male
Improving the Performance of Machine Learning-Based Network Intrusion Detection Systems on the UNSW-NB15 Dataset.
Computational intelligence and neuroscience
Jun 15, 2021
Networks are exposed to an increasing number of cyberattacks due to their vulnerabilities. So, cybersecurity strives to make networks as safe as possible, by introducing defense systems to detect any suspicious activities. However, firewalls and clas...
Prediction of absenteeism in public schools teachers with machine learning.
Revista de saude publica
Jun 14, 2021
OBJECTIVE: To predict the risk of absence from work due to morbidities of teachers working in early childhood education in the municipal public schools, using machine learning algorithms.
A soft voting ensemble classifier for early prediction and diagnosis of occurrences of major adverse cardiovascular events for STEMI and NSTEMI during 2-year follow-up in patients with acute coronary syndrome.
PloS one
Jun 11, 2021
OBJECTIVE: Some researchers have studied about early prediction and diagnosis of major adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this paper proposes a soft voting ensemble classifier (SVE) using machine lear...
Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jun 10, 2021
Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning...
Evaluating machine learning methodologies for identification of cancer driver genes.
Scientific reports
Jun 10, 2021
Cancer is driven by distinctive sorts of changes and basic variations in genes. Recognizing cancer driver genes is basic for accurate oncological analysis. Numerous methodologies to distinguish and identify drivers presently exist, but efficient tool...
Weighing features of lung and heart regions for thoracic disease classification.
BMC medical imaging
Jun 10, 2021
BACKGROUND: Chest X-rays are the most commonly available and affordable radiological examination for screening thoracic diseases. According to the domain knowledge of screening chest X-rays, the pathological information usually lay on the lung and he...
A machine learning approach to predicting risk of myelodysplastic syndrome.
Leukemia research
Jun 8, 2021
BACKGROUND: Early myelodysplastic syndrome (MDS) diagnosis can allow physicians to provide early treatment, which may delay advancement of MDS and improve quality of life. However, MDS often goes unrecognized and is difficult to distinguish from othe...
The application of artificial intelligence methods to gene expression data for differentiation of uncomplicated and complicated appendicitis in children and adolescents - a proof of concept study.
BMC pediatrics
Jun 8, 2021
BACKGROUND: Genome wide gene expression analysis has revealed hints for independent immunological pathways underlying the pathophysiologies of phlegmonous (PA) and gangrenous appendicitis (GA). Methods of artificial intelligence (AI) have successfull...
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