AIMC Topic: ROC Curve

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The accuracy of artificial intelligence in predicting COVID-19 patient mortality: a systematic review and meta-analysis.

BMC medical informatics and decision making
BACKGROUND: The purpose of this paper was to systematically evaluate the application value of artificial intelligence in predicting mortality among COVID-19 patients.

The accuracy of artificial intelligence used for non-melanoma skin cancer diagnoses: a meta-analysis.

BMC medical informatics and decision making
BACKGROUND: With rising incidence of skin cancer and relatively increased mortality rates, an improved diagnosis of such a potentially fatal disease is of vital importance. Although frequently curable, it nevertheless places a considerable burden upo...

Deep Learning for Localized Detection of Optic Disc Hemorrhages.

American journal of ophthalmology
PURPOSE: To develop an automated deep learning system for detecting the presence and location of disc hemorrhages in optic disc photographs.

Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms.

Archives of gynecology and obstetrics
PURPOSE: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated...

Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately.

The international journal of biochemistry & cell biology
OBJECTIVE: The accurate diagnosis of mixed-type gastric cancer from pathology images presents a formidable challenge for pathologists, given its intricate features and resemblance to other subtypes of gastric cancer. Artificial Intelligence has the p...

Deep learning model for predicting the presence of stromal invasion of breast cancer on digital breast tomosynthesis.

Radiological physics and technology
To develop a deep learning (DL)-based algorithm to predict the presence of stromal invasion in breast cancer using digital breast tomosynthesis (DBT). Our institutional review board approved this retrospective study and waived the requirement for inf...

Systematical analysis of underlying markers associated with Marfan syndrome via integrated bioinformatics and machine learning strategies.

Journal of biomolecular structure & dynamics
Marfan syndrome (MFS) is a hereditary disease with high mortality. This study aimed to explore peripheral blood potential markers and underlying mechanisms in MFS via a series bioinformatics and machine learning analysis. First, we downloaded two MFS...

Artificial intelligence for detecting temporomandibular joint osteoarthritis using radiographic image data: A systematic review and meta-analysis of diagnostic test accuracy.

PloS one
In this review, we assessed the diagnostic efficiency of artificial intelligence (AI) models in detecting temporomandibular joint osteoarthritis (TMJOA) using radiographic imaging data. Based upon the PRISMA guidelines, a systematic review of studies...

Multinomial classification of NLRP3 inhibitory compounds based on large scale machine learning approaches.

Molecular diversity
The role of NLRP3 inflammasome in innate immunity is newly recognized. The NLRP3 protein is a family of nucleotide-binding and oligomerization domain-like receptors as well as a pyrin domain-containing protein. It has been shown that NLRP3 may contri...

Heart-Brain 346-7 Score: the development and validation of a simple mortality prediction score for carbon monoxide poisoning utilizing deep learning.

Clinical toxicology (Philadelphia, Pa.)
INTRODUCTION: Acute mortality from carbon monoxide poisoning is 1-3%. The long-term mortality risk of survivors of carbon monoxide poisoning is doubled compared to age-matched controls. Cardiac involvement also increases mortality risk. We built a cl...